Hey guys, I have collected some best **Data Science resources, Machine Learning resources, Deep Learning resources, Python resources, SQL resources, and Statistics resources,** from all around the internet. If you also want to contribute to the community with your resources, contact me.

## Data Science Resources (also includes Machine Learning Resources and Deep Learning Resources):

- 151 Data Science Interview Questions and Answers
- 164 Data Science Interview Questions and Answers
- 120 Data Science Interview Questions and Answers
- Complete 30 Days Data Science Interview Preparation by iNeuron
- Data Science Interview Questions and Answers
- Data Science Interview Questions
- Data Science cheatsheet
- Data science’s main formulae
- 15 In-depth Interviews with Data Scientists
- 50 Machine Learning Interview Questions and Answers
- Mathematics for Machine Learning
- Machine Learning Cheatsheet
- Machine Learning cheatsheet Mini
- Machine Learning course
- Machine Learning for Everyone
- Supervised Learning cheatsheet
- Supervised Machine Learning
- Applying Unsupervised Learning
- Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
- Visual Introduction to Deep Learning
- Calculus for Deep Learning
- Deep Learning
- Deep Learning by Andrew Ng
- Deep Learning Essential Notes by Andrew Ng
- Optimizers used in Deep Learning by Let the Data Confess
- Deep Learning Tips and Tricks
- Visualization cheatsheet
- 100 NLP Questions and Answers
- Speech Recognition With Python
- Azure ML cheatsheet
- Data Engineering cheatsheet
- R programming cheatsheet
- How to Choose the Right Data Visualization

## Python Resources:

- All about Python
- Beginners python cheatsheet
- Top 100 Python Interview Questions
- Top 40 Top Python Interview Q&A
- Python cheat sheet for data science
- 100 Numpy Exercises
- Pandas cheatsheet
- Pandas Exercises
- EDA using Python
- Python for Data Analysis

## SQL Resources:

- Full SQL ebook 221 pages
- SQL notes 166 pages
- SQL cheatsheet 12 pages
- SQL cheatsheet 3 pages
- SQL Joins cheatsheet 3 pages

## Statistics Resources:

- Statistics cheatsheet
- The Cartoon Guide to Statistics
- Analysis of Variance (ANOVA) by Let the Data Confess

## Probability Resources:

## Git Resources:

## Case Studies:

- Netflix – How they use ML to decide what new shows & movies to make.
- Uber – How they use graph theory + ML to find users making fraudulent trips.
- Airbnb – How they track marketing data at scale

## Free Courses from Google:

- Learn Python basics for data analysis
- Data Science Foundations
- Data Science with Python
- Machine Learning Crash Course

## BONUSES:

- Free Course on Deep Learning from Yann Lecunn
- Avatarify • Photorealistic avatars for video-conferencing: Zoom, Skype, Teams. Run local or tunnel through Colab & render your avatar in real-time.

## A visual guide on how to choose the right Database:

With so many options around, choosing the right datastore can be confusing. In this diagram, we can see a selection choice for a datastore based on a use case.

Data can be 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 (𝗦𝗤𝗟 𝘁𝗮𝗯𝗹𝗲 𝘀𝗰𝗵𝗲𝗺𝗮), 𝘀𝗲𝗺𝗶-𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 (𝗝𝗦𝗢𝗡, 𝗫𝗠𝗟, 𝗲𝘁𝗰.), 𝗮𝗻𝗱 𝘂𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 (𝗕𝗹𝗼𝗯). In the case of structured, they can be relational or columnar, while in the case of semi-structured, there is a wide range of possibilities, from key-value to graph.

*Credits – Satish Chandra Gupta*

**NOTE – All the credits for these resources go to their respective owners. None of this work/resources belongs to me. **

**Check out my other machine learning projects, deep learning projects, computer vision projects, NLP projects, Flask projects at machinelearningprojects.net**