Data Science Resources
This list contains free learning resources and Interview resources for Data Science, Machine Learning, Deep Learning, Data Analysis, NLP, Big Data and other Data Science related tools.
Table of Contents :
| No | Section | Link |
|---|---|---|
| 1 | E-books | Click Here |
| 2 | Interview Resources | Click Here |
| 3 | Cheat-Sheets | Click Here |
E-books
| No | Section | Link |
|---|---|---|
| 1 | Data Analysis | Click Here |
| 2 | Data Science | Click Here |
| 3 | Deep Learning | Click Here |
| 4 | Machine Learning | Click Here |
| 5 | Miscellaneous | Click Here |
| 6 | Natural Language Processing | Click Here |
| 7 | Python | Click Here |
| 8 | R | Click Here |
| 9 | SAS | Click Here |
| 10 | SQL | Click Here |
| 11 | Statistics | Click Here |
| 12 | Text Analysis | Click Here |
Data Analysis
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Python for Data Analysis | Wes McKinney | |
| 2 | Think Stats | Allen B. Downey |
Data Science
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Data Science From Scratch | Joel Grus | |
| 2 | Python Data Science Handbook | Jake VanderPlas | |
| 3 | Think Like A Data Scientist | Brian Godsey |
Deep Learning
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Deep Learning | Ian Goodfellow, Yoshua Bengio, Aaron Courville |
Machine Learning
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Hands on Machine Learning with Scikit-Learn, Keras & Tensorflow | Aurélien Géron | |
| 2 | Introduction to Machine Learning | Ethem Alpaydın | |
| 3 | Machine Learning | Tom M. Mitchell | |
| 4 | Machine Learning : A Probabilistic Perspective | Kevin P. Murphy | |
| 5 | Machine Learning Models and Algorithms for Big Data Classification | Shan Sutharan | |
| 6 | Prediction Machines | Ajay Agarwal, Joshua Gans, Avi Goldfarb | |
| 7 | Python Machine Learning | Sebastian Raschka | |
| 8 | Understanding Machine Learning: From Theory to Algorithms | Shai-Shalev Schwatrz, Shai Ben-David |
Miscellaneous
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Beginning Regular Expressions | Andrew Watt | |
| 2 | Ethics of AI | Nick Bostrom, Eliezer Yudkowsky | |
| 3 | Hadoop : The definitive guide | Tom White | |
| 4 | Introduction to AI | Wolfgang Ertel |
Natural Language Processing
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Natural Language Processing with Python | Steven Bird, Ewan Klein & Edward Loper |
Python
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Python Notes for Professionals | - |
R
| No | Title | Author | Link |
|---|---|---|---|
| 1 | A Beginner’s guide to R | Alain F. Zuur, Elena N. Leno, Erik H.W.G Meesters | |
| 2 | R Programming for Data Science | Roger D. Peng |
SAS
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Introduction to Regular Expression in SAS | K. Mathew Windham |
SQL
| No | Title | Author | Link |
|---|---|---|---|
| 1 | SQL for dummies | Allen G. Taylor |
Statistics
| No | Title | Author | Link |
|---|---|---|---|
| 1 | An Introduction to Statistical Learning with Applications in R | Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani | |
| 2 | Head First Statistics | Dawn Griffiths | |
| 3 | Practical Statistics for Data Scientists | Peter Bruce, Andrew Bruce | |
| 4 | Statistical Inference in Data Science | Brian Caffo | |
| 5 | Statistics Unplugged | Sally Caldwell | |
| 6 | Statistics for Buissness and Economics | Anderson Sweeney Williams | |
| 7 | Statistics in Python | Gael Varoquaux | |
| 8 | The Cartoon Guide to Statistics | Larry Gonick, Woollcott Smith | |
| 9 | The Elements of Statistical Learning | Trevor Hastie, Robert Tibshirani, Jerome Friedman |
Text Analysis
| No | Title | Author | Link |
|---|---|---|---|
| 1 | Applied Text Analysis with Python | Benjamin Bengfort, Rebecca Bilbro & Tony Ojeda |
Interview Resources
| No | Title | Link |
|---|---|---|
| 1 | Big-data Analysis Interview Questions | |
| 1 | Data Science Interview Questions | |
| 2 | ML Interview Questions | |
| 3 | ML Interview Questions Part 2 | |
| 4 | Python Interview Questions | |
| 5 | Ultimate Guide to Data Science Interviews |
Cheat Sheets
| No | Title | Link |
|---|---|---|
| 1 | CLI | |
| 2 | Data Exploration in Python | |
| 3 | git | |
| 4 | git for subversion | |
| 5 | Jupter Notebook | |
| 6 | Kubernetes | |
| 7 | Matplotlib | |
| 8 | Pandas | |
| 9 | Pandas DataFrames | |
| 10 | Python3 | |
| 11 | Python basic | |
| 12 | Python intermediate | |
| 13 | Python for Data Science | |
| 14 | Seaborn | |
| 15 | SQL | |
| 16 | VS-code | |
| 17 | Workflow of version control |
How to Contribute
If you find a nice ebook or interview resource or cheatsheet related to Data Science, feel free to fork PythonBooks and add it in a few steps :
- Fork the repository.
- Add your ebook.
- Add Book title, Author and link to the book inside the specified category in alphabetical order in the ReadMe.
- Submit a pull request.
That’s it.
Alternatively, you can send us an email with book infos : ssiddharth408@gmail.com
Thanks per advance 💙!