A balance between knowledge and practical application is required so that professionals are equipped to apply their knowledge to solve industry problems using data and the relevant techniques. Keeping this in mind, Data Science Foundation is enabling a Book of Knowledge (BoK) on methods and techniques in data science encompassing big data analytics and machine learning.
Data Science Knowledge Center
DSF is providing the access to valuable knowledge and resources that helps in developing relevant skill. A repository of various modules on learning the fundamentals and executing analytics techniques in Python and R are available for data science enthusiasts to learn with practical data sets. This repository is growing and getting enriched day by day.
Unlock the power of data and begin your
organization/career transformation.
The data scientists have a big role in explaining the challenges and opportunities of working with data and exploiting the power of data in the real world to the business leaders and users in order to make the data science projects successful and avoid the hype and failures too. The focus, therefore, is to develop the ‘data mindset’ with sound knowledge of theory as well as application of the same.
A data science enthusiast – whether he is a new learner or a professional with industry experience – needs the right path and guidance to prosper in the data world. DSF is enabling them with the right combination of knowledge and skill in the data science domain and guiding them in their journey with the right resources and network. This valuable guidance is accessible to the members of Data Science Foundation in their career path – to learn, contribute and prosper.
Data Inquest
8th International Data Science Summit
Event Date & Time: 26th of February 2021, 6:00 PM
The 8th international Data Science Summit, organized by the DSF International supported by NASSCOM and in partnership with European Industry University Res
View All DS-TalksBook of Knowledge
Book of Knowledge
Coming up: Comprehensive handbook on descriptive statistics, inferential statistics, supervised machine learning, unsupervised machine learning, time series and other topics....
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General Data Science Topics
The Art of Data Science
Another pay-what-you-want book that takes a big-picture view of how to do data science rather than focusing on the technical nitty gritty of statistical or programming techniques.
The Elements of Data Analytic Style
This book by Johns Hopkins professor Jeff Leek is a useful guide for anyone involved with data analysis and covers a lot of the little details you might miss in statistics lessons and textbooks. It’s a pay-what-you-want book, so while you can technically get this one for free, we recommend making a contribution if you can.
Python Data Science Handbook
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages. Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, A Whirlwind Tour of Python: it’s a fast-paced introduction to the Python language aimed at researchers and scientists.
An Introduction to Data Science
This introductory textbook was written by Syracuse professor Jeffrey Stanton, and it covers a lot of the fundamentals of data science and statistics. It also covers some R programming, but sections of it are very worthwhile reading even for those who’re learning Python.
Machine Learning and Big Data
The purpose behind it is to have a balance between theory and implementation for the software engineer to implement machine learning models comfortably without relying too much on libraries. Most of the time the concept behind a model or a technique is simple or intuitive. This book’s attempt is to make the underlying concepts clear.
The Deep Learning textbook
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
Python Crash Course
A complete Hands-On, Project-Based Introduction to Programming
Applied Data Science
Applied Data Science. Explore the theory, languages and concepts of data science while acquiring the Python programming knowledge
Natural Language Processing with Python
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics
Video Highlights
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Resource & Articles
Effect Of “Social Analytics” – Our Digital Identity In Formation
It is not just about “some data” anymore… Data is forming our identity! Though, it is still the data which plays the all-important role but it’s not in the
How To Demystify The Career Challenges Faced By An Analyst?
…“I am looking for a switch in career and want to be an Analyst. How should I start?” … “I want to do certification course in Big Data and Advanced
