Types of recommender systems
•
0 likes•36 views
I have studies and analysed various recommender systems, and their pros and cons. Handy deck if you wish to have an introduction to recommender systems.
Report
Share
Report
Share
Download to read offline
Recommended
Types of recommender systems
I have studies and analysed various recommender systems, and their pros and cons. Handy guide if you wish to have an introduction to recommender systems.
CBintro
1) The document discusses consumer behavior and why it is important to learn about, specifically looking at why consumers choose certain products over others and the reasons and results of their choices.
2) It examines market share and gaps for different products like phones, soft drinks, and clothing to see how well products are meeting consumer needs and where there is room for new product development.
3) The key aspects of consumer behavior it outlines are what, when, where, why, and how consumers choose as well as the thought, decision, and behavior processes involved to understand how to target customer needs and influence their buying decisions.
Ms 61 ignou assignment 2018
This document discusses consumer behavior and related marketing concepts. It defines consumer behavior and explains its scope using examples. It discusses the differences between organizational and individual buying behaviors. It also explains the concepts of learning and its implications for marketing, reference groups and their influence on purchasing behaviors, and culture and subcultures and their relevance for segmenting products like ready-to-eat foods and apparel. Finally, it asks what strategies a marketer of consumer durables would use to address post-purchase feelings of consumers.
How to write the perfect blog post
The document provides guidance on how to write the perfect blog post reviewing a product. It recommends doing thorough product research, crafting an impressive title and overview, writing an introduction tailored to the audience, describing the product details, answering common reader questions, discussing both pros and cons, comparing similar products, including proof of the product's effectiveness, adding a clear call to action, and concluding by recommending whether to use the product. The goal is to provide all essential information and details to help readers decide whether to purchase the item.
Business plan for startups by Mohit Dubey #TiEinstitute April 27 2013
This deck was presented by Mohit Dubey (Carwale) at the #TiEInstitute session for early stage companies in April 2013.
Follow us on twitter : @tiemumbai
Impersonal Recommendation system on top of Hadoop
This document discusses building an impersonal recommendation system using big data. It describes different recommendation approaches like collaborative filtering, knowledge-based, and content-based recommendations. An impersonal recommender provides suggestions without user profiles by analyzing customer purchase histories to find related item associations. The document proposes using Apache Hadoop to store and process large datasets for generating association rules to power recommendations. Elasticsearch would store and serve the rules to power an online recommender evaluation and improvement.
Evaluating the customer needs identification process and finding its effects ...
Customer Needs Identification is a process to determine what customers want a product to do through gathering raw data from customers via interviews, focus groups, and observation. This data is then interpreted to organize customer needs into independent requirements. The goals are to keep products focused on customer needs and identify both explicit and latent needs. Customer needs identification affects concept selection methods by influencing external decisions, product champions, intuition-based choices, multi-voting, order-based production, prototype evaluation, market demand, standard deviation-based design, and overall company focus on factors like quality, cost and capability.
Recommendation system
Recommendation systems provide users with information they may be interested in based on their preferences and interests. They help address the problem of information overload by retrieving desired information for the user based on their preferences or those of similar users. The two main types of recommendation systems are personalized and non-personalized systems. Common techniques used include collaborative filtering, which finds users with similar tastes, and content-based filtering, which recommends items similar to those a user has liked based on item attributes.
Recommended
Types of recommender systems
I have studies and analysed various recommender systems, and their pros and cons. Handy guide if you wish to have an introduction to recommender systems.
CBintro
1) The document discusses consumer behavior and why it is important to learn about, specifically looking at why consumers choose certain products over others and the reasons and results of their choices.
2) It examines market share and gaps for different products like phones, soft drinks, and clothing to see how well products are meeting consumer needs and where there is room for new product development.
3) The key aspects of consumer behavior it outlines are what, when, where, why, and how consumers choose as well as the thought, decision, and behavior processes involved to understand how to target customer needs and influence their buying decisions.
Ms 61 ignou assignment 2018
This document discusses consumer behavior and related marketing concepts. It defines consumer behavior and explains its scope using examples. It discusses the differences between organizational and individual buying behaviors. It also explains the concepts of learning and its implications for marketing, reference groups and their influence on purchasing behaviors, and culture and subcultures and their relevance for segmenting products like ready-to-eat foods and apparel. Finally, it asks what strategies a marketer of consumer durables would use to address post-purchase feelings of consumers.
How to write the perfect blog post
The document provides guidance on how to write the perfect blog post reviewing a product. It recommends doing thorough product research, crafting an impressive title and overview, writing an introduction tailored to the audience, describing the product details, answering common reader questions, discussing both pros and cons, comparing similar products, including proof of the product's effectiveness, adding a clear call to action, and concluding by recommending whether to use the product. The goal is to provide all essential information and details to help readers decide whether to purchase the item.
Business plan for startups by Mohit Dubey #TiEinstitute April 27 2013
This deck was presented by Mohit Dubey (Carwale) at the #TiEInstitute session for early stage companies in April 2013.
Follow us on twitter : @tiemumbai
Impersonal Recommendation system on top of Hadoop
This document discusses building an impersonal recommendation system using big data. It describes different recommendation approaches like collaborative filtering, knowledge-based, and content-based recommendations. An impersonal recommender provides suggestions without user profiles by analyzing customer purchase histories to find related item associations. The document proposes using Apache Hadoop to store and process large datasets for generating association rules to power recommendations. Elasticsearch would store and serve the rules to power an online recommender evaluation and improvement.
Evaluating the customer needs identification process and finding its effects ...
Customer Needs Identification is a process to determine what customers want a product to do through gathering raw data from customers via interviews, focus groups, and observation. This data is then interpreted to organize customer needs into independent requirements. The goals are to keep products focused on customer needs and identify both explicit and latent needs. Customer needs identification affects concept selection methods by influencing external decisions, product champions, intuition-based choices, multi-voting, order-based production, prototype evaluation, market demand, standard deviation-based design, and overall company focus on factors like quality, cost and capability.
Recommendation system
Recommendation systems provide users with information they may be interested in based on their preferences and interests. They help address the problem of information overload by retrieving desired information for the user based on their preferences or those of similar users. The two main types of recommendation systems are personalized and non-personalized systems. Common techniques used include collaborative filtering, which finds users with similar tastes, and content-based filtering, which recommends items similar to those a user has liked based on item attributes.
recommendationsystem-140410131156-phpapp01 (1).pdf
Recommendation systems provide users with information they may be interested in based on their preferences and interests. They help address the problem of information overload by retrieving desired information for the user based on their preferences or those of similar users. The two main types of recommendation systems are personalized and non-personalized systems. Common techniques used include collaborative filtering, which finds users with similar tastes, and content-based filtering, which recommends items similar to those a user has liked based on item attributes.
New Product Assessment - Shopper-Aha
This document outlines a methodology for assessing the potential of a new product in the Australian market in 3-4 weeks. It involves 3 main steps: 1) Understanding market dynamics and opportunities through online interviews; 2) Examining implications for shelf placement through in-store videos; 3) Gathering feedback on the product concept. An optional 4th step involves in-home product trials. The goal is to provide a fast, cost-effective evaluation of a product's opportunity and optimize its launch strategy.
Elements of production planning for goods and services
This document discusses elements of production planning for goods and services. It begins by defining what a product is from a marketing perspective, focusing on customer satisfaction rather than physical components. It then differentiates between goods and services, noting that most products contain both tangible and intangible elements. The document outlines several consumer and business product classes that can help inform marketing strategy planning based on how customers view and purchase different types of products. Key decisions like branding, packaging, and pricing are also discussed.
idea2MVP template
how do you move from an Idea to developing a product or a service ? what are the steps you need to go through. The template provides you with a step by step process
Cb ppt
The document discusses various concepts related to consumer behaviour research. It describes the key concepts of the production concept, product concept, selling concept, and marketing concept in the development of marketing. It also discusses consumer decision making models and different approaches to consumer research including quantitative and qualitative paradigms. Finally, it outlines various research methods for collecting primary data such as surveys, experiments, depth interviews, focus groups, and projective techniques.
Evaluating the customer needs identification process and finding its effects ...
Evaluating the customer needs identification process and finding its effects on concept selection and concept testing procedure.
ADM6274 - Final (NEHA)
Personalized marketing creates individualized messages for consumers by using automated processes and customer-centric recommendation engines. It allows customers to customize products to their specifications. By offering consumers products they already want, businesses are more likely to convert visits to sales. Personalized marketing represents customers by finding them through their behavior and integrated channels, using owned big data and fact-based decisions. Recommender systems seek to predict user preferences and provide recommendations for items similar to a user's profile or items liked by similar users. Content-based filtering uses a user's profile while collaborative filtering matches users with similar tastes. Knowledge-based systems use defined rules or similarity measures to meet user requirements. Hybrid systems combine approaches to solve cold start problems and better adapt to changing
Young marketers elite 2013 assignment 2.1 - tuong_phong
Apple needs to research the market, customers, and competitors before launching a new product. Specifically, Apple should understand the demographics and needs of the target market, customer behaviors and locations, and competitors' strengths and weaknesses. Apple examines the product development process from establishing needs to determining the future of older products. For a new product launch, Apple will research current and potential customers through surveys to understand reactions, barriers to purchase, price expectations, and what is most attractive about the product. The research will help Apple segment the market and successfully launch the new product.
Customer Value Proposition
The document discusses creating customer value propositions. It defines a customer value proposition as describing the experiences a target user will have when purchasing and using a product. It should compare the product to the next best alternative for the target user. The customer value proposition identifies: the timeframe of when value will be delivered; the key target user; how the user and alternative are profiled; the value experiences of benefits, trade-offs and parity; how value is quantified; and how the proposition guides product marketing activities. Developing an accurate customer value proposition requires understanding the target user and alternative in detail.
Haas 2009 Riemer Weigend
The document provides guidance on product marketing in a Web 2.0 world. It discusses the importance of understanding customer insights, having a clear value proposition, positioning the product against competitors, telling a story about the product through marketing communications, considering the whole customer experience, seeking customer feedback, and adapting business models and communication channels.
Chapter 11 the product and developing new products
This document discusses the seven phases of new product development: 1) New product strategy development, 2) Idea generation, 3) Product screening and evaluation, 4) Business analysis, 5) Product development, 6) Test marketing, and 7) Commercialization. It provides details on each phase, including generating ideas from marketing and research sources, evaluating ideas using checklists, concept testing with potential buyers, analyzing business factors like costs and market potential, developing prototypes, test marketing products, and commercial product launch. The overall process aims to efficiently develop new products that meet market needs and are viable business opportunities.
Mini-training: Personalization & Recommendation Demystified
Recommendations are everywhere : music, movies, books, social medias, e-commerce web sites… The Web is leaving the era of search and entering one of discovery. This quick introduction will help you to understand this vast topic and why you should use it.
recommendation system techunique and issue
This document discusses recommendation system techniques and issues. It covers common recommendation approaches like content-based filtering, collaborative filtering, and hybrid systems. It also addresses challenges like cold start problems, privacy issues, and data sparsity. Recommendation systems analyze user preferences to suggest new items, and are used by applications like ecommerce sites, streaming services, and social networks to provide personalized recommendations. While useful, they also present technical challenges for researchers.
Web personalization
Web personalization involves customizing content for individual users based on their behavior and preferences. There are three main methods of personalization: implicit, which monitors user search history and details; explicit, which allows users to select their interests; and hybrid, which combines implicit and explicit. Personalization aims to provide relevant information to users without requiring explicit requests, using content-based filtering of user profiles or social/collaborative filtering based on interests of similar users. Combining social and content-based filtering with an item ontology can improve recommendations for sparse user data.
Product Management Guide - A Work In Progress
This is a "live" document where I regularly put some learnings about product management from different sources
HubSpot Presentation Q3 8-11-15
This document summarizes a presentation given to the Knoxville HubSpot User Group (HUG) about mapping content to the buyer's journey. The presentation defines the three stages of the buyer's journey - awareness, consideration, and decision. It provides a methodology for mapping different types of content like eBooks and case studies to each stage based on user behavior and keywords. An example is given of a potential customer named Violet who needs help deciding between landscapers. The presentation recommends providing her with a targeted email and landing page in the decision stage to help validate her choice. It stresses the importance of meeting customers with the right content at each point in their journey.
Module 2 (1).pptx
The document provides information on product mix, product line, product life cycle, branding, and marketing strategies at different stages of the product life cycle. It defines a product mix as the set of all product lines and items offered by a seller. A product line refers to a unique product category or brand offered that are closely related. The four stages of a product's life cycle are introduction, growth, maturity, and decline. Marketing strategies vary at each stage, from promotion to raise awareness in introduction to price cuts in decline. Branding helps create consumer preference and loyalty for a product.
case based recommendation approach for market basket data
Recommender systems have become an important part of various applications in e-commerce, supporting both customers and providers in their decision-making processes. However, these systems still must overcome limitations that reduce their performance, like recommendations overspecialization, less popular item providing, and difficulties when items with unequal probability distribution appear or recommendations for sets of items are asked. A novel approach, addressing the above issues through a case-based recommendation methodology is presented here. The scope of the presented approach is to generate meaningful recommendations based on items' co-occurring patterns and to provide more insight into customers' buying habits. In contrast to current recommendation techniques that recommend items based on users' ratings or history, and to most case-based item recommenders that evaluate items' similarities, the implemented recommender uses a hierarchical model for the items and searches for similar sets of items, in order to recommend those that are most likely to satisfy a user.
Product Development and Microfinance
Lecture from 2012 for Princeton Woodrow Wilson School Lecture on Product development and Microfinance.
The following table shows data from a fictional cohort study of in.docx
The following table shows data from a fictional cohort study of industrial workers followed over 30 years to see if exposure to industrial organic solvent affects cognitive function adversely. Use the information below for the following question.
Organic Solvent Exposure
Number of Participants
Impaired Function
Yes
28654
818
No
71346
649
Total
100000
1467
Calculate and interpret the risk of impaired function in participants exposed to organic solvents and those who were not.
1
COM5111
Product Policy
Week 5 SemB 2019-20
2
Learning Objectives
1. What are the characteristics of products, and how do marketers classify product?
2. How can companies differentiate products?
3. Why is product design important, and what are the different approaches taken?
4. How can a company build and manage its product mix and product lines?
5. How can marketers best manage luxury brands?
6. What environmental issues must marketers consider in their product strategies?
7. How can companies combine products to create strong co-brands or ingredient
brands?
8. How can companies use packaging, labeling, warranties, and guarantees as
marketing tools?
3
Components Of The Market Offering
Marketing planning begins with formulating an offering to meet target customers’ needs or wants
customer will judge the offering
on three basic elements
Slide 15 & 16 Slide 17
4
Product Characteristics
and Classifications
• Product
– Anything that can be offered to a market to satisfy a want or need,
including physical goods, services, experiences, events, persons,
places, properties, organizations, information, and ideas
https://www.youtube.com/watch?v=xYjoBAUOjTk
5
Characteristics of Winning Products
A unique superior product—
a differentiated product that delivers unique benefits and a
compelling value proposition to the customer or user—
is the number one driver of new-product profitability
Source: Robert G. Cooper, Winning at New Products: Creating Value through Innovation (New York: Basic Books, 2011), p. 32.
How about your individual assignment?
6
Unique and superior products tend to have the followings in
common
1. are superior to competitors’ products in terms of meeting users’ needs
2. solve a problem the customer has with a competitive product
3. feature good value for the money and excellent price and performance
characteristics
4. provide excellent product quality, according to customers’ way of defining quality
5. offer features easily perceived as useful by the customer
6. offer benefits that are highly visible to the customer
Source: Robert G. Cooper, Winning at New Products: Creating Value through Innovation (New York: Basic Books, 2011), p. 33.
7
Product Levels: The Customer-Value Hierarchy
• The Five Product Levels
The service or benefit
the customer
is really buying
e.g. rest & sleep
The marketer must
turn the core benefit
into a basic product
e.g. bed, bathroom …
A set of attributes
and c.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
More Related Content
Similar to Types of recommender systems
recommendationsystem-140410131156-phpapp01 (1).pdf
Recommendation systems provide users with information they may be interested in based on their preferences and interests. They help address the problem of information overload by retrieving desired information for the user based on their preferences or those of similar users. The two main types of recommendation systems are personalized and non-personalized systems. Common techniques used include collaborative filtering, which finds users with similar tastes, and content-based filtering, which recommends items similar to those a user has liked based on item attributes.
New Product Assessment - Shopper-Aha
This document outlines a methodology for assessing the potential of a new product in the Australian market in 3-4 weeks. It involves 3 main steps: 1) Understanding market dynamics and opportunities through online interviews; 2) Examining implications for shelf placement through in-store videos; 3) Gathering feedback on the product concept. An optional 4th step involves in-home product trials. The goal is to provide a fast, cost-effective evaluation of a product's opportunity and optimize its launch strategy.
Elements of production planning for goods and services
This document discusses elements of production planning for goods and services. It begins by defining what a product is from a marketing perspective, focusing on customer satisfaction rather than physical components. It then differentiates between goods and services, noting that most products contain both tangible and intangible elements. The document outlines several consumer and business product classes that can help inform marketing strategy planning based on how customers view and purchase different types of products. Key decisions like branding, packaging, and pricing are also discussed.
idea2MVP template
how do you move from an Idea to developing a product or a service ? what are the steps you need to go through. The template provides you with a step by step process
Cb ppt
The document discusses various concepts related to consumer behaviour research. It describes the key concepts of the production concept, product concept, selling concept, and marketing concept in the development of marketing. It also discusses consumer decision making models and different approaches to consumer research including quantitative and qualitative paradigms. Finally, it outlines various research methods for collecting primary data such as surveys, experiments, depth interviews, focus groups, and projective techniques.
Evaluating the customer needs identification process and finding its effects ...
Evaluating the customer needs identification process and finding its effects on concept selection and concept testing procedure.
ADM6274 - Final (NEHA)
Personalized marketing creates individualized messages for consumers by using automated processes and customer-centric recommendation engines. It allows customers to customize products to their specifications. By offering consumers products they already want, businesses are more likely to convert visits to sales. Personalized marketing represents customers by finding them through their behavior and integrated channels, using owned big data and fact-based decisions. Recommender systems seek to predict user preferences and provide recommendations for items similar to a user's profile or items liked by similar users. Content-based filtering uses a user's profile while collaborative filtering matches users with similar tastes. Knowledge-based systems use defined rules or similarity measures to meet user requirements. Hybrid systems combine approaches to solve cold start problems and better adapt to changing
Young marketers elite 2013 assignment 2.1 - tuong_phong
Apple needs to research the market, customers, and competitors before launching a new product. Specifically, Apple should understand the demographics and needs of the target market, customer behaviors and locations, and competitors' strengths and weaknesses. Apple examines the product development process from establishing needs to determining the future of older products. For a new product launch, Apple will research current and potential customers through surveys to understand reactions, barriers to purchase, price expectations, and what is most attractive about the product. The research will help Apple segment the market and successfully launch the new product.
Customer Value Proposition
The document discusses creating customer value propositions. It defines a customer value proposition as describing the experiences a target user will have when purchasing and using a product. It should compare the product to the next best alternative for the target user. The customer value proposition identifies: the timeframe of when value will be delivered; the key target user; how the user and alternative are profiled; the value experiences of benefits, trade-offs and parity; how value is quantified; and how the proposition guides product marketing activities. Developing an accurate customer value proposition requires understanding the target user and alternative in detail.
Haas 2009 Riemer Weigend
The document provides guidance on product marketing in a Web 2.0 world. It discusses the importance of understanding customer insights, having a clear value proposition, positioning the product against competitors, telling a story about the product through marketing communications, considering the whole customer experience, seeking customer feedback, and adapting business models and communication channels.
Chapter 11 the product and developing new products
This document discusses the seven phases of new product development: 1) New product strategy development, 2) Idea generation, 3) Product screening and evaluation, 4) Business analysis, 5) Product development, 6) Test marketing, and 7) Commercialization. It provides details on each phase, including generating ideas from marketing and research sources, evaluating ideas using checklists, concept testing with potential buyers, analyzing business factors like costs and market potential, developing prototypes, test marketing products, and commercial product launch. The overall process aims to efficiently develop new products that meet market needs and are viable business opportunities.
Mini-training: Personalization & Recommendation Demystified
Recommendations are everywhere : music, movies, books, social medias, e-commerce web sites… The Web is leaving the era of search and entering one of discovery. This quick introduction will help you to understand this vast topic and why you should use it.
recommendation system techunique and issue
This document discusses recommendation system techniques and issues. It covers common recommendation approaches like content-based filtering, collaborative filtering, and hybrid systems. It also addresses challenges like cold start problems, privacy issues, and data sparsity. Recommendation systems analyze user preferences to suggest new items, and are used by applications like ecommerce sites, streaming services, and social networks to provide personalized recommendations. While useful, they also present technical challenges for researchers.
Web personalization
Web personalization involves customizing content for individual users based on their behavior and preferences. There are three main methods of personalization: implicit, which monitors user search history and details; explicit, which allows users to select their interests; and hybrid, which combines implicit and explicit. Personalization aims to provide relevant information to users without requiring explicit requests, using content-based filtering of user profiles or social/collaborative filtering based on interests of similar users. Combining social and content-based filtering with an item ontology can improve recommendations for sparse user data.
Product Management Guide - A Work In Progress
This is a "live" document where I regularly put some learnings about product management from different sources
HubSpot Presentation Q3 8-11-15
This document summarizes a presentation given to the Knoxville HubSpot User Group (HUG) about mapping content to the buyer's journey. The presentation defines the three stages of the buyer's journey - awareness, consideration, and decision. It provides a methodology for mapping different types of content like eBooks and case studies to each stage based on user behavior and keywords. An example is given of a potential customer named Violet who needs help deciding between landscapers. The presentation recommends providing her with a targeted email and landing page in the decision stage to help validate her choice. It stresses the importance of meeting customers with the right content at each point in their journey.
Module 2 (1).pptx
The document provides information on product mix, product line, product life cycle, branding, and marketing strategies at different stages of the product life cycle. It defines a product mix as the set of all product lines and items offered by a seller. A product line refers to a unique product category or brand offered that are closely related. The four stages of a product's life cycle are introduction, growth, maturity, and decline. Marketing strategies vary at each stage, from promotion to raise awareness in introduction to price cuts in decline. Branding helps create consumer preference and loyalty for a product.
case based recommendation approach for market basket data
Recommender systems have become an important part of various applications in e-commerce, supporting both customers and providers in their decision-making processes. However, these systems still must overcome limitations that reduce their performance, like recommendations overspecialization, less popular item providing, and difficulties when items with unequal probability distribution appear or recommendations for sets of items are asked. A novel approach, addressing the above issues through a case-based recommendation methodology is presented here. The scope of the presented approach is to generate meaningful recommendations based on items' co-occurring patterns and to provide more insight into customers' buying habits. In contrast to current recommendation techniques that recommend items based on users' ratings or history, and to most case-based item recommenders that evaluate items' similarities, the implemented recommender uses a hierarchical model for the items and searches for similar sets of items, in order to recommend those that are most likely to satisfy a user.
Product Development and Microfinance
Lecture from 2012 for Princeton Woodrow Wilson School Lecture on Product development and Microfinance.
The following table shows data from a fictional cohort study of in.docx
The following table shows data from a fictional cohort study of industrial workers followed over 30 years to see if exposure to industrial organic solvent affects cognitive function adversely. Use the information below for the following question.
Organic Solvent Exposure
Number of Participants
Impaired Function
Yes
28654
818
No
71346
649
Total
100000
1467
Calculate and interpret the risk of impaired function in participants exposed to organic solvents and those who were not.
1
COM5111
Product Policy
Week 5 SemB 2019-20
2
Learning Objectives
1. What are the characteristics of products, and how do marketers classify product?
2. How can companies differentiate products?
3. Why is product design important, and what are the different approaches taken?
4. How can a company build and manage its product mix and product lines?
5. How can marketers best manage luxury brands?
6. What environmental issues must marketers consider in their product strategies?
7. How can companies combine products to create strong co-brands or ingredient
brands?
8. How can companies use packaging, labeling, warranties, and guarantees as
marketing tools?
3
Components Of The Market Offering
Marketing planning begins with formulating an offering to meet target customers’ needs or wants
customer will judge the offering
on three basic elements
Slide 15 & 16 Slide 17
4
Product Characteristics
and Classifications
• Product
– Anything that can be offered to a market to satisfy a want or need,
including physical goods, services, experiences, events, persons,
places, properties, organizations, information, and ideas
https://www.youtube.com/watch?v=xYjoBAUOjTk
5
Characteristics of Winning Products
A unique superior product—
a differentiated product that delivers unique benefits and a
compelling value proposition to the customer or user—
is the number one driver of new-product profitability
Source: Robert G. Cooper, Winning at New Products: Creating Value through Innovation (New York: Basic Books, 2011), p. 32.
How about your individual assignment?
6
Unique and superior products tend to have the followings in
common
1. are superior to competitors’ products in terms of meeting users’ needs
2. solve a problem the customer has with a competitive product
3. feature good value for the money and excellent price and performance
characteristics
4. provide excellent product quality, according to customers’ way of defining quality
5. offer features easily perceived as useful by the customer
6. offer benefits that are highly visible to the customer
Source: Robert G. Cooper, Winning at New Products: Creating Value through Innovation (New York: Basic Books, 2011), p. 33.
7
Product Levels: The Customer-Value Hierarchy
• The Five Product Levels
The service or benefit
the customer
is really buying
e.g. rest & sleep
The marketer must
turn the core benefit
into a basic product
e.g. bed, bathroom …
A set of attributes
and c.
Similar to Types of recommender systems (20)
recommendationsystem-140410131156-phpapp01 (1).pdf
recommendationsystem-140410131156-phpapp01 (1).pdf
Elements of production planning for goods and services
Elements of production planning for goods and services
Evaluating the customer needs identification process and finding its effects ...
Evaluating the customer needs identification process and finding its effects ...
Young marketers elite 2013 assignment 2.1 - tuong_phong
Young marketers elite 2013 assignment 2.1 - tuong_phong
Chapter 11 the product and developing new products
Chapter 11 the product and developing new products
Mini-training: Personalization & Recommendation Demystified
Mini-training: Personalization & Recommendation Demystified
case based recommendation approach for market basket data
case based recommendation approach for market basket data
The following table shows data from a fictional cohort study of in.docx
The following table shows data from a fictional cohort study of in.docx
Recently uploaded
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
原版一模一样【微信：741003700 】【(uts毕业证书)悉尼科技大学毕业证学历证书】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
The Ipsos - AI - Monitor 2024 Report.pdf
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
Experts live - Improving user adoption with AI
Bekijk de slides van onze sessie Enhancing Modern Workplace Efficiency op Experts Live 2024.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
Global Situational Awareness of A.I. and where its headed
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
毕业原版【微信:176555708】【(UMN毕业证书)明尼苏达大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
The Building Blocks of QuestDB, a Time Series Database
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
一比一原版(UO毕业证)渥太华大学毕业证如何办理
UO毕业证录取书【微信95270640】购买（渥太华大学毕业证成绩单硕士学历）Q微信95270640代办UO学历认证留信网伪造渥太华大学学位证书精仿渥太华大学本科/硕士文凭证书补办渥太华大学 diplomaoffer,Transcript购买渥太华大学毕业证成绩单购买UO假毕业证学位证书购买伪造渥太华大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括 烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。
文凭办理流程：
1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：微信95270640我们有专业老师帮你查询）；
2开始安排制作毕业证成绩单电子图；
3毕业证成绩单电子版做好以后发送给您确认；
4毕业证成绩单电子版您确认信息无误之后安排制作成品；
5成品做好拍照或者视频给您确认；
6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。
7完成交易删除客户资料
高精端提供以下服务：
一：渥太华大学渥太华大学毕业证文凭证书全套材料从防伪到印刷水印底纹到钢印烫金
二：真实使馆认证（留学人员回国证明）使馆存档
三：真实教育部认证教育部存档教育部留服网站可查
四：留信认证留学生信息网站可查
五：与学校颁发的相关证件1:1纸质尺寸制定（定期向各大院校毕业生购买最新版本毕,业证成绩单保证您拿到的是鲁昂大学内部最新版本毕业证成绩单微信95270640）
A.为什么留学生需要操作留信认证?
留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时多
在线办理(英国UCA毕业证书)创意艺术大学毕业证在读证明一模一样
学校原件一模一样【微信：741003700 】《(英国UCA毕业证书)创意艺术大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
一比一原版(Harvard毕业证书)哈佛大学毕业证如何办理
毕业原版【微信:41543339】【(Harvard毕业证书)哈佛大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
毕业原版【微信:176555708】【(GWU,GW毕业证书)乔治·华盛顿大学毕业证】【微信:176555708】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
DSSML24_tspann_CodelessGenerativeAIPipelines
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
State of Artificial intelligence Report 2023
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
一比一原版(Chester毕业证书)切斯特大学毕业证如何办理
毕业原版【微信:41543339】【(Chester毕业证书)切斯特大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
→ 【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！
Recently uploaded (20)
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...
Challenges of Nation Building-1.pptx with more important
Challenges of Nation Building-1.pptx with more important
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...
Types of recommender systems
- 2. What is the Purpose? 1. Substitutes: Does your visitor know what he wants to buy but can’t find it? Are there suitable substitute products you could present? 2. Complements: Your visitor knows what he wants to buy and has it in his basket. Are there complementary add-on products you should be presenting to increase his satisfaction and your sales? 3. Ideas: Your customer is browsing for new items in which he might be interested. What are the products that he’s most likely to purchase? 4. Sequence: Frequently the order in which multiple recommendations are presented is important in maximizing satisfaction. This is called order of consumption. What is the right order of consumption for your items? Order also encompasses emphasis. If you are presenting pictures of 10 alternate shirts or shoes, which should be given prominence on the page?
- 3. What is the Environment? 1. Movies, books, and music – huge rapidly changing inventories for immediate consumption. 2. Electronics or hardware - large but more stable inventories with very large subcategories of complimentary and supplementary choices and many different buyer objectives and motives. 3. Women’s clothing – large fast changing inventories with far fewer attributes for making objective or hard comparisons but a very large number of sub-attributes like color and size.
- 4. 5 Types of Recommenders (in order of increasing complexity) 1. Most Popular Item 2. Association and Market Basket Models 3. Content Filtering 4. Collaborative Filtering 5. Hybrid Models
- 5. 1. Most Popular Item ● Simply offer what is most popular. ● Very little data requirements. Just sales figures. ● Non-personalized. ● Can be personalized according to category preferences of the user (eg. if the user is interested in books->novel, recommend the most popular or the latest release novel)
- 6. 2. Association or Market Basket Analysis ● Identifies group of items consumed together. (Eg: {bananas, apples, oranges} , {jalapenos, avocados}, {beer,diapers}) ● Other items of the group can be recommended if the user has consumed one item in that group. ● Non-personalized. ● Simple and fast. Data Prep is minimal. ● Will not work well where the selection is extremely broad like in music compared to the users. However, its performance might be improved by using other filters.
- 7. 3. Content Filtering ● Very intuitive. Gives same features to content and the user. Matches the user with the content that has similar feature values. ● Solves the ‘cold-start’ problem in recommenders. ● But, It is difficult and most of the times cost-ineffective to learn and maintain the features for the user and the inventory, especially when they are fast changing. ● Pandora Radio uses CF with 400 attributes.
- 8. 4. Collaborative Filtering ● Finds users similar to the given user and recommends other items that are consumed by those users. ● Can recommend items without the human-designated understanding of the items itself. ● It is only meaningful with large amount of user base. ● It will not satisfy the needs of users who have a unique taste. ● Items that are new and have never been consumed/rated cannot be recommended since recommendation relies on prior rating (‘Cold-start problem’).
- 9. 5. Hybrid Recommender ● Knowledge Based Recommender involves the addition of rules by human subject matter experts. Good Product Marketing Managers can frequently define what products do and do not go together. ● Hybrid Recommenders involve combining different recommenders according to different business cases. ● Netflix uses a hybrid CB/CF recommender. It offers both recommendations based on the habits of similar customers (Collaborative Filtering) as well as recommendations based on highly rated films seen to be similar by content attributes (Content Filtering). ● It is likely that the optimum recommender will be a hybrid.
- 10. Deep Learning and Recommenders ● Image Recognition techniques can be used to create new features. ● Addition of the new attribute allowed He and McAuley to improve overall recommender performance by 10% to 26% on different clothing categories, and by 25% to 45% for ‘cold start’ previously unseen customers. They have a commercial version called Fashionista. Read the original study here. ● Adding attributes allows Content Filtering. And, content filtering is the solution to ‘Cold-Start’ problem.
- 11. Thank You! Please, provide your feedback on postforshubham@gmail.com .