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ML & DS Guide

Complied Resources for learning Machine Learning & Data Science

This list is continuously updated - And if you have some good suggestions or resources to share, create pull request and contribute.

Table of Contents

Guide

Maths

Main Topics & Detailed Syllabus :

Data Science Libs

Major/Imp Libs are Numpy, Pandas, Matplotlib, Seaborn,

Mini Project #1

Data Analysis Using Data Science Libraries

Machine Learning Beginner Courses

Take Up few Beginner Courses to learn about the fundamentals of ML Models, ML Algorithms, Data Processing Technique, Model Evaluation etc .

Mini Projects #2

  • Regression :
    • Boston House Price Prediction
  • Classification :
    • Iris Classification
    • Red Wine Quality
  • Clustering :
    • Customer Segmentation

Data Science Stuff

Machine Learning Stuff

Read in Details about the ML Algorithms from Books mentioned below

  • Machine Learning Algorithms
    • Supervised ML Algorithms
      • Linear Regression:
        • Basics :
        • Tutorial :
        • Implementation :
        • Application :
      • Logistic Regression:
      • Decision Tree:
      • Naive Bayes
      • KNN
      • Random Forest:
      • AdaBoost
      • Gradient Boosting
        • GBM
        • XGBoost:
        • LightGBM
        • CatBoost
    • Unsupervised ML Algo
      • Clustering
        • K Means
        • DBSSCAN
        • Hierarchal Clustering
      • Dimensionality Reduction
        • PCA
        • LDA
        • Kernel PCA
    • Reinforcement
      • Deep Q Networks
      • Deep Deterministic Policy Gradient
      • A3C Algo
      • Q Learning
  • Model Evaluation :
  • Model Selection
  • Hyper Parameter Tuning
  • Pipeline
  • Model Deployment :

Final Projects

Projects Ideas , Guide & Tutorial

  1. ML-ProjectKart
  2. 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
  3. Simplilearn
  4. Data Flair
  5. KDNuggets
  6. Upgrad
  7. Crio
  8. Analyticsindiamag

Online Course, Books & YT Playlists

Books

  1. Introduction to Machine Learning with Python: A Guide for Data Scientists
  2. Hands–On Machine Learning with Scikit–Learn and TensorFlow
  3. An Introduction to Statistical Learning
  4. The Elements of Statistical Learning
  5. Practical Statistics for Data Scientists: 50 Essential Concepts

Courses

  1. Google ML Crash Course
  2. Udemy Machine Learning A-Z™: Hands-On Python & R In Data Science|
  3. Udacity Machine Learning by Georgia Tech
  4. Udacity Machine Learning
  5. Udacity Machine Learning Engineer NanoDegree
  6. Yorko Open Machine Learning Course
  7. DataQuest Platform
  8. DataCamp Platform

YT Playlist

  1. Machine Learning —Andrew Ng
  2. StatQuest with Josh Starmer
  3. Abhishek Thakur 30 Days of ML
  4. Ranji Raj

Commonly Used Websites and YT Channels

Websites

  1. EliteDataScience
  2. Kaggle
  3. TowardsDataScience
  4. Medium
  5. AnalyticsVidhya
  6. Datacamp
  7. DataQuest

YT Channels

  1. Artificial Intelligence - All in One
  2. DigitalSreeni
  3. Kaggle
  4. 3Blue1Brown
  5. DeepLearningAI
  6. Two Minute Papers
  7. Machine Learning TV
  8. RANJI RAJ
  9. Data School
  10. Keith Galli
  11. Daniel Bourke
  12. StatQuest with Josh Starmer
  13. Data Professor
  14. Krish Naik
  15. Sentdex

Other's Roadmap/Guides & Resources

  1. Applied ML
  2. Approaching ML Problem
  3. Data Science Res
  4. ML for Software Engineers
  5. ML Course
  6. ML Cheatsheet
  7. ML Projects
  8. Learning
  9. ML Algo Implementation
  10. Detail ML Tutorials
  11. Awesome Data Science
  12. Microsoft DataScience
  13. Microsoft ML
  14. TowardsDataScience 52 week Curriculum to become Data Scientist