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
