The document discusses predictive analytics and business analytics. It provides definitions of business analytics and its components including descriptive, predictive, and prescriptive analytics. Examples of how various companies have used analytics for competitive advantage are provided. The role of data and analytics in decision making is explored through examples such as Florence Nightingale's analysis of the causes of cholera outbreak. A framework for data-driven decision making including problem identification, data collection, preprocessing, model building, and communication is also summarized.
Career Prospects and Scope of Data Science in Indiaachaljain11
Data Science refers to the theories, collective processes, concepts, technologies and tools that help to analyze, review and extract key information from raw data.
In today’s business terms, data science is all about using the raw data to make better decisions and generate business value.
My class presentation at USC. It gives an introduction about what is data science, machine learning, applications, recommendation system and infrastructure.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
In this Lunch & Learn session, Chirag Jain gives us a friendly & gentle introduction to Machine Learning & walks through High-Level Learning frameworks using Linear Classifiers.
Career Prospects and Scope of Data Science in Indiaachaljain11
Data Science refers to the theories, collective processes, concepts, technologies and tools that help to analyze, review and extract key information from raw data.
In today’s business terms, data science is all about using the raw data to make better decisions and generate business value.
My class presentation at USC. It gives an introduction about what is data science, machine learning, applications, recommendation system and infrastructure.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
In this Lunch & Learn session, Chirag Jain gives us a friendly & gentle introduction to Machine Learning & walks through High-Level Learning frameworks using Linear Classifiers.
Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Getting started on your natural language processing project? First you'll need to extract some features from your corpus. Frequency, Syntax parsing, word vectors are good ones to start with.
Extension of this method exists in recent paper here: https://arxiv.org/ftp/arxiv/papers/1708/1708.05712.pdf
Overview and tutorial of Morse-Smale regression prior to a new paper coming out exploring this idea further. It is a topologically-based piecewise regression method for supervised learning.
Evolution of Data Analytics: the past, the present and the futureVarun Nemmani
This paper delves into the topic of advanced analytics, the current industry demands to utilize and analyze huge/diverse amounts of data, how big data analytics is becoming a part of the decision making process and to anticipate trends. This paper takes the reader from Analytics era 1.0 to the current Analytics era 3.0; shows the future projections of big data analytics and also the current leaders of the Big Data Analytics market.
Data Science Training | Data Science For Beginners | Data Science With Python...Simplilearn
This Data Science presentation will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.
This Data Science presentation will cover the following topics:
1. What is Data Science?
2. Who is a Data Scientist?
3. What does a Data Scientist do?
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its largelibrary of mathematical functions.
Learn more at: https://www.simplilearn.com
Create Success with Analytics: Predictive Analytics 101: Your Roadmap to Driv...Aggregage
Predictive analytics is an increasingly common buzzword with many forms. It seems everyone has their own take on what it is and which best practices and business benefits apply.
What does predictive analytics really mean? We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value.
Create Success with Analytics: Predictive Analytics 101: Your Roadmap to Driv...Hannah Flynn
Predictive analytics is an increasingly common buzzword with many forms. It seems everyone has their own take on what it is and which best practices and business benefits apply.
What does predictive analytics really mean? We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value.
Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
Data Science is a form of science that focuses on dealing with huge chunks of data by using modern data analysis tools and techniques to discover hidden patterns, meaningful insights, and make critical business decisions.
A Data Science professional has to utilize complicated machine learning algorithms to develop predictive models. There could be multiple sources present in different formats used in data analysis.
Getting started on your natural language processing project? First you'll need to extract some features from your corpus. Frequency, Syntax parsing, word vectors are good ones to start with.
Extension of this method exists in recent paper here: https://arxiv.org/ftp/arxiv/papers/1708/1708.05712.pdf
Overview and tutorial of Morse-Smale regression prior to a new paper coming out exploring this idea further. It is a topologically-based piecewise regression method for supervised learning.
Evolution of Data Analytics: the past, the present and the futureVarun Nemmani
This paper delves into the topic of advanced analytics, the current industry demands to utilize and analyze huge/diverse amounts of data, how big data analytics is becoming a part of the decision making process and to anticipate trends. This paper takes the reader from Analytics era 1.0 to the current Analytics era 3.0; shows the future projections of big data analytics and also the current leaders of the Big Data Analytics market.
Data Science Training | Data Science For Beginners | Data Science With Python...Simplilearn
This Data Science presentation will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.
This Data Science presentation will cover the following topics:
1. What is Data Science?
2. Who is a Data Scientist?
3. What does a Data Scientist do?
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:
1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its largelibrary of mathematical functions.
Learn more at: https://www.simplilearn.com
Create Success with Analytics: Predictive Analytics 101: Your Roadmap to Driv...Aggregage
Predictive analytics is an increasingly common buzzword with many forms. It seems everyone has their own take on what it is and which best practices and business benefits apply.
What does predictive analytics really mean? We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value.
Create Success with Analytics: Predictive Analytics 101: Your Roadmap to Driv...Hannah Flynn
Predictive analytics is an increasingly common buzzword with many forms. It seems everyone has their own take on what it is and which best practices and business benefits apply.
What does predictive analytics really mean? We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value.
An introduction to BRIDGEi2i - Analytics Solutions company focused on solving complex based problems based on data mining and advanced analytics on big data. Visit http://www.bridgei2i.com
Using Machine Learning to Accelerate Revenue Paul Johnston
This presentation explains what Machine Learning is and the use cases for Machine Learning within sales & marketing. Learn how to use Machine Learning to improve conversions, clone your best customers, improve sales performance and reduce customer churn.
Is AnalyticsOps the weak link in your data strategy?Wiiisdom
"Four out of five CEOs do not trust the data upon which they base their decisions."
For many years, insight-driven organizations have understood the importance of data in decision-making. They have also understood the importance of data governance by having invested heavily in DataOps technologies. However, the problem of trust persists. In this session, you will discover how to better govern the last mile on the data journey, de-risk Analytics, and thus ensure user trust.
Watch the session here: https://youtu.be/FOd5nswyGSY
People, process, platform, presented by Adam SingerSocialMedia.org
In his Brands-Only Summit Pre-Conference presentation, Google's Adam Singer shares how to build a smart, flexible analytics organization.
He talks about how getting the right people, implementing the right processes, and using the right technology platform will help you stay current in measuring marketing and sales performance.
How to Run a Data Driven Product Dev Organization by Skedulo CPMProduct School
In this presentation, learn about where to start in the data & analytics journey or, if you’re already on this journey, tips on making it more successful so your good product can become great with data & analytics.
Main takeaways:
-The vast majority of Product Managers don't have the knowledge or direct experience using data to inform development
-Learn how companies evolve from an idea in a garage to data juggernauts
-Understand the data tools available to Product Managers and how to adapt your organization to use them
The change in the buyer’s journey has dramatically shifted the way marketers work. With marketers taking increasing ownership over pipeline, there is unprecedented pressure for marketers to target more effectively and to create more meaningful campaign touches.
But how do you know who to target and what kind of interaction is most meaningful for them? Most importantly, how can you maximize the impact of each interaction? With data. Join EverString and Lionbridge for a live discussion on how to uncover hidden pipeline by leveraging data and predictive modeling.
Using Data Science to Build an End-to-End Recommendation SystemVMware Tanzu
We get recommendations everyday: Facebook recommends people we should connect with; Amazon recommends products we should buy; and Google Maps recommends routes to take. What all these recommendation systems have in common are data science and modern software development.
Recommendation systems are also valuable for companies in industries as diverse as retail, telecommunications, and energy. In a recent engagement, for example, Pivotal data scientists and developers worked with a large energy company to build a machine learning-based product recommendation system to deliver intelligent and targeted product recommendations to customers to increase revenue.
In this webinar, Pivotal data scientist Ambarish Joshi will take you step-by-step through the engagement, explaining how he and his Pivotal colleagues worked with the customer to collect and analyze data, develop predictive models, and operationalize the resulting insights and surface them via APIs to customer-facing applications. In addition, you will learn how to:
- Apply agile practices to data science and analytics.
- Use test-driven development for feature engineering, model scoring, and validating scripts.
- Automate data science pipelines using pyspark scripts to generate recommendations.
- Apply a microservices-based architecture to integrate product recommendations into mobile applications and call center systems.
Presenters: Ambarish Joshi and Jeff Kelly, Pivotal
Your Roadmap, Your Product Story & Datadriven Product ManagementProduct School
From this presentation you will find out more about becoming a Data-Driven Product Manager.
Get a FREE copy of our Product Book here: https://prdct.school/2BSES8J
Artificial Intelligence using Machine Learning techniques like Churn and Recommender models can help Relationship Managers connect with dormant clients and help recommend stocks and MFs using existing applications via different devices
Embedded analytics: The future of Business IntelligenceAnil Kumar Saini
In this talk we will see whether we are building our first product or revamping an existing one, embedded analytics can help us solve real customer problems, which builds product value and creates a competitive differentiator to propel our business forward. Also, we'll deeply look into how Embedded Analytics is differnet from Traditional Business Intelligence and what are the factors/trends driving Embedded Analytics.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
27. London Cholera Outbreak - 1854
Severe outbreak of cholera that occurred near Broad Street (now Broad wick
street) in Soho district of London in 1854.
More than 500 people died within 10 days of the outbreak, the mortality rate in
some parts of the city was as high as 12.8%.