This document summarizes Jay Wang's background and experience in machine learning and data science. It then discusses several applications of machine learning including personalized recommendation in retail using data from companies like Stitch Fix, sources of data, and how algorithms interact with users. Finally, it covers topics like data-centric startups, building competitive advantages with data, applications of machine learning, and the advertising process at Twitter including targeting, filtering, click-through rate prediction, and ranking/pricing models.
Competitive Intelligence - How To Track Your CompetitorsBuzzSumo
Overview of how to use SEMrush adn BuzzSumo to comprehensively track your competitors. Includes how to track:
Keyword performance
Content performance
Ad strategy
Amplifiers (who shares & links to content)
Also how to set up alerts to be notified daily on new competitor content, mentions of them and links to them.
14 Actionable, Low-Cost Growth Hacks For Startups on Startupsauce.comRyan Wardell
This slideshow is from the "Growth Hacking Like A Pirate" presentation I made in February 2014 at Blue Chilli - a leading Sydney-based startup incubator.
Visit startupsauce.com for a detailed breakdown of how each hack works, and how you can replicate it.
Competitive Intelligence - How To Track Your CompetitorsBuzzSumo
Overview of how to use SEMrush adn BuzzSumo to comprehensively track your competitors. Includes how to track:
Keyword performance
Content performance
Ad strategy
Amplifiers (who shares & links to content)
Also how to set up alerts to be notified daily on new competitor content, mentions of them and links to them.
14 Actionable, Low-Cost Growth Hacks For Startups on Startupsauce.comRyan Wardell
This slideshow is from the "Growth Hacking Like A Pirate" presentation I made in February 2014 at Blue Chilli - a leading Sydney-based startup incubator.
Visit startupsauce.com for a detailed breakdown of how each hack works, and how you can replicate it.
Behavioral Targeting and Audience Analysis for NetworksJordan Mitchell
The next giant step in ad optimization centers around people and their behavior. Others Online offers a drop-dead-simple behavioral profiling and targeting Web service that shows large online media companies what their audience cares about, allowing them to better understand, segment, target and monetize their audience.
Take your analytics to the next level with closed-loop marketing! Effective marketers should be able to tie every single lead; customer and dollar back to the marketing initiative that created them. That is the power of closed-loop marketing.
Closed-loop marketing cuts through the widespread vagueness of marketing myths and assumptions and reveals real data about the success (or failure) of your marketing efforts.
Download our "Introduction to Closed-Loop Marketing" guide to take the blindfolds off and focus on actual results rather than fuzzy metrics.
By reading this ebook, you will gain:
A clear understanding of how closed-loop marketing works
6 tips on becoming a better marketer by closing the loop
Details on how to fix your loop if you spot something odd in it
A presentation by Brad Kleinman of WorkSmart-eMarketing on email marketing for continuing education professionals. This presentation was delivered via webinar for the eMarketing Techniques Webinar SEries on 2/12/2009.
The Digital Marketing world is expansive and as a startup founder, small business owner, or eCommerce shop owner, it can be overwhelming when you are trying to learn what tools to use or how to use them. This presentation gets down to the basics of digital marketing across email channels, paid advertising, content, influencer, and social media, and provides some basic terms to understand as you begin your foray into the world of marketing.
Digital Marketing Strategy for Your BusinessNetroStar
The way people interact and communicate has changed drastically in recent years. Our daily lives are completely different than they were ten to fifteen years ago and you, as a business manager, have to adjust to the current situation.
“Traditional” marketing techniques aren't enough to take your business to the top. That part isn't really news. If you're trying to do a little bit of web marketing, though, you've probably noticed that your Facebook page, Twitter account, and website aren’t getting quite as much attention as you hoped for, if any at all. Some people just throw up their hands in frustration and swear off the Internet marketing in general at this point, but the web isn't the problem here. The issue is that, while you might be doing some kind of digital marketing, you've got no strategy to speak of.
Here is why having a solid digital strategy is vital to achieving success on the web for your business.
In this presentation, Shubham introduces SMAC and associated trends. Shubham's interest area lies in the creation of SMAC supported intelligent stores in retail.
Youtube link to this presentation:
https://www.youtube.com/watch?v=hiYwa2ZDlCc&list=PLpWwJcYzFoIQDt3v59RKfflKJOq8UV5c6
This video focuses on the mechanics of Facebook marketing. The meat of these slides is based on the components of Facebook providing a look at what can be collected, analyzed, etc.
Facebook Marketing: A Comprehensive Guide for Beginners
Brief intro Facebook Marketing
Don't forget to share this video to your friends.
Subscribe to Our youtube channel.
Official FB page: facebook.com/reconnectt/
Advanced Social Media Strategies for Business Jamie Siracusa
Welcome to our "Advanced Social Media Strategies" webinar. How to- planning, solutions and checklists for proper implementation of Social Media campaigns for South Jersey business owners.
RealTime Marketing and Loyalty+ Platform - RML+PTVS Next
http://blissadtech.com/rml+p/
Bliss AdTech is a global digital solutions organization and system integrator for automated and real time digital marketing platforms.
Bliss AdTech builds its unique innovative platform called Real Time Marketing and Loyalty + Platform (RML+P) over the base platform of Plumb5.
RML+P offers unique loyalty management solutions that helps businesses to Retain and Grow with customers.
RML+P is a amalgamation of Consulting + Implementation + Integration + Customization + Maintenance and Support.
Cities and Startups: Cultivating Deep EngagementCode for America
Cities and Startups: Cultivating Deep Engagement
FastFWD, City of Philadelphia
Story Bellows, co-director of the Philadelphia Mayor's Office of New Urban Mechanics
Watch the video online: https://www.youtube.com/watch?v=PRKUCCHj-08&list=PL65XgbSILalVoej11T95Tc7D7-F1PdwHq&index=4
Get involved with Code for America: www.codeforamerica.org/action
In this presentation, we’ll go over real-world use cases of Machine Learning and Artificial Intelligence in web and mobile applications, and we’ll explain how they work. We’ll discuss opportunities for startups in all domains to create value from data (big or small) and to create innovative, predictive features in their applications.
We’ll review existing technologies that make Machine Learning accessible, in particular with automatic selection of algorithms, auto-tuning of parameters, and auto-scaling. Deep Learning (a subset of Machine Learning techniques which is getting a lot of press due to recent advances and successes) is also being made accessible without costly hardware and, in certain cases, without requiring specialized knowledge.
The main message for developers is that they can easily use the power of machine intelligence without having to rely on a team of Data Scientists. This will be illustrated in more detail with concrete use cases: priority detection and image categorization.
Ultra brief and ultra draft overview of investor's look at machine learning / deep learning startups by Victor Osyka of Almaz Capital, https://www.linkedin.com/in/victorosyka or http://fb.com/victor.osika
Behavioral Targeting and Audience Analysis for NetworksJordan Mitchell
The next giant step in ad optimization centers around people and their behavior. Others Online offers a drop-dead-simple behavioral profiling and targeting Web service that shows large online media companies what their audience cares about, allowing them to better understand, segment, target and monetize their audience.
Take your analytics to the next level with closed-loop marketing! Effective marketers should be able to tie every single lead; customer and dollar back to the marketing initiative that created them. That is the power of closed-loop marketing.
Closed-loop marketing cuts through the widespread vagueness of marketing myths and assumptions and reveals real data about the success (or failure) of your marketing efforts.
Download our "Introduction to Closed-Loop Marketing" guide to take the blindfolds off and focus on actual results rather than fuzzy metrics.
By reading this ebook, you will gain:
A clear understanding of how closed-loop marketing works
6 tips on becoming a better marketer by closing the loop
Details on how to fix your loop if you spot something odd in it
A presentation by Brad Kleinman of WorkSmart-eMarketing on email marketing for continuing education professionals. This presentation was delivered via webinar for the eMarketing Techniques Webinar SEries on 2/12/2009.
The Digital Marketing world is expansive and as a startup founder, small business owner, or eCommerce shop owner, it can be overwhelming when you are trying to learn what tools to use or how to use them. This presentation gets down to the basics of digital marketing across email channels, paid advertising, content, influencer, and social media, and provides some basic terms to understand as you begin your foray into the world of marketing.
Digital Marketing Strategy for Your BusinessNetroStar
The way people interact and communicate has changed drastically in recent years. Our daily lives are completely different than they were ten to fifteen years ago and you, as a business manager, have to adjust to the current situation.
“Traditional” marketing techniques aren't enough to take your business to the top. That part isn't really news. If you're trying to do a little bit of web marketing, though, you've probably noticed that your Facebook page, Twitter account, and website aren’t getting quite as much attention as you hoped for, if any at all. Some people just throw up their hands in frustration and swear off the Internet marketing in general at this point, but the web isn't the problem here. The issue is that, while you might be doing some kind of digital marketing, you've got no strategy to speak of.
Here is why having a solid digital strategy is vital to achieving success on the web for your business.
In this presentation, Shubham introduces SMAC and associated trends. Shubham's interest area lies in the creation of SMAC supported intelligent stores in retail.
Youtube link to this presentation:
https://www.youtube.com/watch?v=hiYwa2ZDlCc&list=PLpWwJcYzFoIQDt3v59RKfflKJOq8UV5c6
This video focuses on the mechanics of Facebook marketing. The meat of these slides is based on the components of Facebook providing a look at what can be collected, analyzed, etc.
Facebook Marketing: A Comprehensive Guide for Beginners
Brief intro Facebook Marketing
Don't forget to share this video to your friends.
Subscribe to Our youtube channel.
Official FB page: facebook.com/reconnectt/
Advanced Social Media Strategies for Business Jamie Siracusa
Welcome to our "Advanced Social Media Strategies" webinar. How to- planning, solutions and checklists for proper implementation of Social Media campaigns for South Jersey business owners.
RealTime Marketing and Loyalty+ Platform - RML+PTVS Next
http://blissadtech.com/rml+p/
Bliss AdTech is a global digital solutions organization and system integrator for automated and real time digital marketing platforms.
Bliss AdTech builds its unique innovative platform called Real Time Marketing and Loyalty + Platform (RML+P) over the base platform of Plumb5.
RML+P offers unique loyalty management solutions that helps businesses to Retain and Grow with customers.
RML+P is a amalgamation of Consulting + Implementation + Integration + Customization + Maintenance and Support.
Cities and Startups: Cultivating Deep EngagementCode for America
Cities and Startups: Cultivating Deep Engagement
FastFWD, City of Philadelphia
Story Bellows, co-director of the Philadelphia Mayor's Office of New Urban Mechanics
Watch the video online: https://www.youtube.com/watch?v=PRKUCCHj-08&list=PL65XgbSILalVoej11T95Tc7D7-F1PdwHq&index=4
Get involved with Code for America: www.codeforamerica.org/action
In this presentation, we’ll go over real-world use cases of Machine Learning and Artificial Intelligence in web and mobile applications, and we’ll explain how they work. We’ll discuss opportunities for startups in all domains to create value from data (big or small) and to create innovative, predictive features in their applications.
We’ll review existing technologies that make Machine Learning accessible, in particular with automatic selection of algorithms, auto-tuning of parameters, and auto-scaling. Deep Learning (a subset of Machine Learning techniques which is getting a lot of press due to recent advances and successes) is also being made accessible without costly hardware and, in certain cases, without requiring specialized knowledge.
The main message for developers is that they can easily use the power of machine intelligence without having to rely on a team of Data Scientists. This will be illustrated in more detail with concrete use cases: priority detection and image categorization.
Ultra brief and ultra draft overview of investor's look at machine learning / deep learning startups by Victor Osyka of Almaz Capital, https://www.linkedin.com/in/victorosyka or http://fb.com/victor.osika
SUPERSMART LEARNING TOOLS for Lean Startups: Volume 1 - Six Question (Q) Temp...Rod King, Ph.D.
Fast Validated Learning is at the core of the Lean Startup Method. However, learning and mastering the Lean Startup Method is a time-consuming, arduous, and expensive venture. The main reason is that Lean Startup tools are developed, learned, and applied using a Fragmented Learning approach. There is an exponential increase in the number of Lean Startup tools. However, Lean Startup tools hardly talk to each other; they do not share a register or common vocabulary of topics,
Question-tags are very powerful tools for organizing and managing ideas as well as tools in any methodology including the Lean Startup Method. In this presentation, six question-tags and basic templates are presented. These question-tags and templates can be used as the basic building blocks or "atoms" for creating tools ("molecules" and "compounds") for Universal Problem Solving & Project Management (UPSPM). In other words, the presented blank and annotated Question (Q)-Templates can be used for discovering, solving, and managing problems in every domain.
For Lean Startups, these Q-Templates are the basic tools for effectively as well as efficiently organizing and managing Lean Startup projects. These Q-Templates can be put together to function like any Lean Startup tool' for instance, Validation Board, Value Proposition Canvas, Business Model Canvas, and Lean Canvas. Also, all business tools can be deconstructed or decomposed using the Q-Templates.
Investors foresee a safe bet on deep tech startupseTailing India
Indian deep technology start-ups have become the most sought after bets for angels and venture capital (VC) funds for their potential to scale up rapidly and be able to offer an opportunity for early exit for the investors.
Self-Service.AI - Pitch Competition for AI-Driven SaaS StartupsDatentreiber
SELF-SERVICE.AI IN A NUTSHELL
Background:> artificial intelligence enables SaaS companies to build intelligent self-service solutions for complex tasks such as customer service, personal scheduling, dynamic pricing, ad targeting etc.
Objective:> provide a networking platform for AI-driven SaaS start-ups to present their product and team to high profile clients, partners and investors by organizing a start-up pitch competition.
Audience:> start-ups from any country worldwide at any given stage with a Software-as-a-Service product that uses artificial intelligence (i.e. machine & deep learning, predictive & prescriptive analytics etc.) to provide a self-service solution for companies or consumers that solve a concrete business problem or serve a certain need.
Examples:> existing AI-driven SaaS startups are e.g.: Clarifai, x.ai, Api.ai, Versium, Gpredictive, collectAI, trbo, DigitalGenius, DataMinr and many more to come.
Recommender Systems and Active Learning (for Startups)Neil Rubens
This presentation presents a high level overview of recommender systems and active learning, including from the viewpoint of startups vs. established companies, the cold-start problem, etc.
Investor's view on machine intelligence startups, 2.0, Jan 2017Victor Osyka
Updated deeper overview of investor's look at machine learning / deep learning startups, with slight Russian accent. =)
Some slides are courtesy of Russia.ai and personally great friend @Petr Zhegin:
#23, #28 are from http://www.russia.ai/single-post/2016/09/21/Ten-Russian-speaking-venture-capital-funds-one-may-consider-to-back-an-AI-startup
#30 insights are from http://www.slideshare.net/RussiaAI/artificial-intelligence-investment-trends-and-applications-h1-2016
Victor Osyka of Almaz Capital, http://fb.com/victor.osika, http://medium.com/@victorosyka
Deep learning in production with the bestAdam Gibson
Getting deep learning adopted at your company. The current landscape of academia vs industry. Presentation at AI with the best (online conference):
http://ai.withthebest.com/
BootstrapLabs - Tracxn Report - artificial intelligence for the Applied Arti...BootstrapLabs
This report covers companies that provide the infrastructure for creating Artificial Intelligence. These Infrastructure companies include those working on Machine Learning, Deep Learning based platforms, libraries. Some of theses companies also provide platforms for Natural Language Processing and Visual Recognition. In the Applications section, the report covers companies leveraging AI techniques to build applications tailored for end use in Enterprise, Industry & Consumer sectors.
Over $1B has been invested in AI-Infrastructure startups since 2010 with ¬$340M being invested in 2015. Over $7.5B has been invested in AI-Applications startups since 2010 with $2.3B being invested in 2015.
This is the slide that Terry. T. Um gave a presentation at Kookmin University in 22 June, 2014. Feel free to share it and please let me know if there is some misconception or something.
(http://t-robotics.blogspot.com)
(http://terryum.io)
Scalable Data Science and Deep Learning with H2O
In this session, we introduce the H2O data science platform. We will explain its scalable in-memory architecture and design principles and focus on the implementation of distributed deep learning in H2O. Advanced features such as adaptive learning rates, various forms of regularization, automatic data transformations, checkpointing, grid-search, cross-validation and auto-tuning turn multi-layer neural networks of the past into powerful, easy-to-use predictive analytics tools accessible to everyone. We will present a broad range of use cases and live demos that include world-record deep learning models, anomaly detection tools and approaches for Kaggle data science competitions. We also demonstrate the applicability of H2O in enterprise environments for real-world customer production use cases.
By the end of the hands-on-session, attendees will have learned to perform end-to-end data science workflows with H2O using both the easy-to-use web interface and the flexible R interface. We will cover data ingest, basic feature engineering, feature selection, hyperparameter optimization with N-fold cross-validation, multi-model scoring and taking models into production. We will train supervised and unsupervised methods on realistic datasets. With best-of-breed machine learning algorithms such as elastic net, random forest, gradient boosting and deep learning, you will be able to create your own smart applications.
A local installation of RStudio is recommended for this session.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
How to win data science competitions with Deep LearningSri Ambati
Note: Please download the slides first, otherwise some links won't work!
How to win kaggle style data science competitions and influence decisions with R, Deep Learning and H2O's fast algorithms.
We take a few public and kaggle datasets and model to win competitions on accuracy and scoring speed.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
H2O Distributed Deep Learning by Arno Candel 071614Sri Ambati
Deep Learning R Vignette Documentation: https://github.com/0xdata/h2o/tree/master/docs/deeplearning/
Deep Learning has been dominating recent machine learning competitions with better predictions. Unlike the neural networks of the past, modern Deep Learning methods have cracked the code for training stability and generalization. Deep Learning is not only the leader in image and speech recognition tasks, but is also emerging as the algorithm of choice in traditional business analytics.
This talk introduces Deep Learning and implementation concepts in the open-source H2O in-memory prediction engine. Designed for the solution of enterprise-scale problems on distributed compute clusters, it offers advanced features such as adaptive learning rate, dropout regularization and optimization for class imbalance. World record performance on the classic MNIST dataset, best-in-class accuracy for eBay text classification and others showcase the power of this game changing technology. A whole new ecosystem of Intelligent Applications is emerging with Deep Learning at its core.
About the Speaker: Arno Candel
Prior to joining 0xdata as Physicist & Hacker, Arno was a founding Senior MTS at Skytree where he designed and implemented high-performance machine learning algorithms. He has over a decade of experience in HPC with C++/MPI and had access to the world's largest supercomputers as a Staff Scientist at SLAC National Accelerator Laboratory where he participated in US DOE scientific computing initiatives. While at SLAC, he authored the first curvilinear finite-element simulation code for space-charge dominated relativistic free electrons and scaled it to thousands of compute nodes.
He also led a collaboration with CERN to model the electromagnetic performance of CLIC, a ginormous e+e- collider and potential successor of LHC. Arno has authored dozens of scientific papers and was a sought-after academic conference speaker. He holds a PhD and Masters summa cum laude in Physics from ETH Zurich.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Transform your Business with AI, Deep Learning and Machine LearningSri Ambati
Video: https://www.youtube.com/watch?v=R3IXd1iwqjc
Meetup: http://www.meetup.com/SF-Bay-ACM/events/231709894/
In this talk, Arno Candel presents a brief history of AI and how Deep Learning and Machine Learning techniques are transforming our everyday lives. Arno will introduce H2O, a scalable open-source machine learning platform, and show live demos on how to train sophisticated machine learning models on large distributed datasets. He will show how data scientists and application developers can use the Flow GUI, R, Python, Java, Scala, JavaScript and JSON to build smarter applications, and how to take them to production. He will present customer use cases from verticals including insurance, fraud, churn, fintech, and marketing.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
AI and Machine Learning in Digital Marketing.pdfAmyDonovan18
Grow your business with the help of the best digital marketing training institute in Bangalore. NIDM's digital marketing classes in Bangalore specialize in: Search Engine Optimization, Search Engine Marketing, Social Media Marketing, Web Designing, Graphic Designing, and more! If you're a student, you get a 100% placement guarantee upon course completion.
How to use Online Marketing Technology to Improve Campaign Performance - Lowe...Online Marketing Summit
How to use Online Marketing Technology to Improve Campaign Performance
This session will share practical suggestions for getting the most out of the available online marketing technologies including web analytics, ad exchange management and search marketing bid management.
* Dawn Deal, Online Marketing Manager, Lowes.com
* Jeff Campbell, VP, Account Director, Resolution Media. (@CJeffCampbell)
The Future of AI in Digital Marketing Transforming Customer Experiences.pdfAdsy
Can AI help marketers understand users better?
That's what we want to figure out in this presentation.
Firstly, let's see how AI can help with personalization. Also, let's see how artificial intelligence can help with user engagement.
Sure thing, we will talk about ethical concerns regarding AI.
But overall, you need to know that more and more companies use AI in their daily activities.
Presentation made at Wazzap? Lithuania by Meelis Ojasild from Altex internet marketing.
More info about Altex and internet marketing services:
http://www.altex.ee
If job boards died - where would you get your candidates?Jobs2web
This was a presentation by Doug Berg at the OnRec/Kennedy conference in Chicago where he shared how employers could use interactive marketing for recruiting versus just using job boards.
El impacto del big data en la estrategia de los medios de comunicacion by Osc...ACTUONDA
El impacto del Big Data en la estrategia de negocio de los medios de comunicación
Oscar Mendez (CEO, Stratio)
@omendezsoto @stratioDB
Primer encuentro BIG MEDIA
Conectando Media, Audiencia y Publicidad con Datos
24 de junio 2014, Madrid
• Sponsor Platinum : Perfect Memory
• Sponsor Gold : Stratio, Paradigma
• Con el apoyo de : Big Data Spain, Medios On
• Socio tecnológico : Agora News
• Organizadores : Actuonda y Cátedra Big Data UAM-BM
• Contacto : Nicolas Moulard (Actuonda) moulard@actuonda.com @Radio_20
www.bigmediaconnect.es
Using AdWords as a research tool through analyzing the potential keywords your customers are searching for. There is also a discussion of how to understand your website from an action/task perspective, and targeting strategies for your audience.
SALESmanago: Buyer Persona in Marketing Automationsalesmanago
Buyer Persona is a fictional character, representing features of your customers. It represents human face of customer. Such representations make it easier to segment customers, design Buyer's Journey and plan Lead Nurturing.
Thank you to all who attended our Internet Marketing Seminar at Automation Alley on February 9th, 2010. We hope that you found value in our experience and discussions.
An investment-worthy internet marketing campaign includes a combination of traditional methods while strategically utilizing various digital methods including search engine marketing, social media marketing and content distribution. For more information on Biznet please visit: http://www.biznetis.net
The talk has three parts : the first part gives an overview of data science work, including roadmap of data science team, responsibility and value of data scientists; the second part talks about pitfalls in analysis and teaches some common analysis methods; the third part takes decision support, metrics and AB testing as examples to explain the data science work and how they are translated to business value.
Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...Jay (Jianqiang) Wang
this talk discusses combining Statistics and Expert Human Judgment for Better Recommendations. we start by the business model of stitch fix and then go on to talk about the life of a fix. then how we build clothing recommendation systems that are used by human stylists. eventually we discuss selection biases and how to account for selection biases.
Making data-informed decisions and building intelligent products (Chinese)Jay (Jianqiang) Wang
this talk is presented in Mandarin Chinese. In this talk, i discuss how to make data-informed decisions and build data-driven engineering culture. I also cover stitch fix, which is a AI-driven fashion company. I go over various aspects of the business and data challenges.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Notes on Machine Learning and Data-centric Startups
1. Jianqiang (Jay) Wang
Stitch fix/twitter/HP Labs
July 26, 2015
Notes on Machine Learning and
data centric startups
2. About me
B.S. degree in Management Science; Ph.D. in Statistics;
Data scientist in Stitch Fix (retail recommendation);
Data scientist in twitter (computational ads algo);
HP Labs : Business optimization (pricing & portfolio
management, marketing)
Consulting:
SpotTrender (video-pretesting)
Brilent (data science training, recruiter products)
Data-centric businesses (advertising, retail,...).
5. Sources of data
sold flag, survey ratings
Unstructured : feedback, request note,
style image
6. How should interact with algorithms to
Recommend clothes
perform analytics
Medical diagnostics
Human-computer interaction
7. Data-centric startups
Jet.com Amazon killer: subscription-based retail, Marc
Lore (Diapers.com), $50/yr, 5-10% lower price
Thumbtacks Service provider referral (how to monetize?)
SpotTrender Pre-test video commercials
Sano Realtime news discovery from social
networks (twitter, instagram, weibo, VK, ..)
Common
crawl
(non-profit) Open repo of web crawl data,
billions of pages each month
8. ML applications
Search engines
Computational advertising
Recommender systems
Adaptive websites : (learn user preference, personalized webpage)
Medical diagnosis
Human-computer interaction;
Computational finance/stock market analysis;
Computer vision, object recognition,
Speech and handwriting recognition
Machine Translation
Fraud detection (internet, credit card)
Game playing
Information retrieval
Natural language processing
14. Advertiser campaigns
Supply (platform users) vs demand (advertisers)
Creating your own campaign
Tweet engagement
Followers
App install
Website visits
Lead generation
15. Targeting
Targeting criteria
Keywords (tweet or tweet engagement)
Interests
Followers : (similar) followers of a handle
Tailored audiences
How to match users to targeting criteria
Interest/age prediction: we don’t ask the users to explicitly indicate their
interests/age but infer them from who they follow and what they tweet about.
Algorithm & analytics
Interest (NLP), age (classification)
16. Filtering ad candidates
Campaigns currently active with budget left
Same advertiser/tweet fatigue rules
How many times per week for the same user?
How to make such decisions?
Dismiss/block/spam filters
17. Click through rate (CTR) prediction
How likely is the user to ...
Click on the url
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Online machine learning with 10k+ features
User request and candidate features
Request : user geo, user type, login frequency, interest,..
Ad : advertiser vertical, popularity, tweet content
Model fitting & diagnostics
18. Ranking
Second price auction on Expected Cost per Impression
(ECPI)
Advertisers bid for engagement (Bid)
Predicated engagement rate (pCTR)
Naïve ranking function : ECPI=Bid * pCTR
Pricing
Minimum bid required to win auction
Winner has (bidCPE1, pCTR1), runner-up has (bidCPE2, pCTR2)
Winner pays paidCPE = bidCPE2 * pCTR2 / pCTR1