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
  • Data Science Libs
  • Mini Project #1
  • Machine Learning Beginner Courses
  • Mini Projects #2
  • Data Science Stuff
  • Machine Learning Stuff
  • Final Projects
• Projects Ideas , Guide & Tutorial
• Online Course, Books & YT Playlists
  • Books
  • Courses
  • YT Playlist
• Commonly Used Websites and YT Channels
  • Websites
  • YT Channels
• Other's Roadmap/Guides & Resources

Guide

Maths

Main Topics & Detailed Syllabus :

• [ ] Linear Algebra :
  • [ ] Essence of Linear Algebra by 3blue1brown
  • [ ] GFG Articles for LA
• [ ] Calculus :
  • [ ] Essence of Linear Calculus by 3blue1brown
  • [ ] GFG Articles for Calculus
• [ ] Stats :
  • [ ] Statistics - A Full University Course on Data Science Basics
  • [ ] GFG Articles for Statistics
• [ ] Probability :
  • [ ] GFG Articles for Probability

Data Science Libs

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

• [ ] Numpy :
  • [ ] Video Tutorial: Numpy Crash Course
  • [ ] Practice: Numpy 100Q
  • [ ] Docs: Numpy Docs
• [ ] Pandas :
  • [ ] Video Tutorial: Pandas Crash Course
  • [ ] Tutorial/Course with Practice labs: Kaggle Course
  • [ ] Practice: Pandas 100Q
  • [ ] Docs: Pandas Docs
• [ ] Matplotlib :
  • [ ] Video Tutorial: Matplotlib Crash Course
  • [ ] Practice :
    • [ ] 11 Plots to plot
    • [ ] Matplotlib Exercise
  • [ ] Docs : Matplotlib Docs
• [ ] Seaborn :
  • [ ] Tutorial :
    • [ ] Seaborn Crash Course
    • [ ] Elite Data Science Seaborn-tutorial
  • [ ] Practice :
    • [ ] Seaborn Olympics Dataset Kernel
    • [ ] TowardDataScience Practical Data Analysis
    • [ ] Kaggle Data Viz Course
  • [ ] Docs : Seaborn Docs

Mini Project #1

Data Analysis Using Data Science Libraries

• [ ] Guided Project :
  • [ ] Solving real world data science tasks with Python Pandas!
  • [ ] Solving Real World Business Question
  • [ ] Solving real world data science tasks 2
• [ ] Self Guided Project :
  • [ ] Investigating-Netflix-Movies-and-Guest-Stars-in-The-Office
    • [ ] Investigating-Netflix-Movies-and-Guest-Stars-in-The-Office Qanhnn12
    • [ ] Investigating-Netflix-Movies-and-Guest-Stars-in-The-Office anthonymanotoa
  • [ ] Check Data Analysis DataCamp Projects

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 .

• [ ] Kaggle Intro to Machine Learning
• [ ] Kaggle Intermediate Machine Learning
• [ ] Andrew Ng ML Course
• [ ] Udemy A-Z Machine Learning Course
• [ ] Sentdex ML Course
• [ ] Microsoft ML-For-Beginners
• [ ] Scikit Learn ML Course

Mini Projects #2

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

Data Science Stuff

• [ ] Data Collection
  • [ ] DataSets :
    • [ ] PapersWithCode Datasets
    • [ ] Kaggle Datasets
    • [ ] UCI Datasets
    • [ ] Google Dataset Search
    • [ ] AWS Open Data Search
    • [ ] Wiki's List of Datasets
  • [ ] API :
    • [ ] APIs for Beginners - How to use an API
  • [ ] Scraping :
    • [ ] BeautifulSoup
    • [ ] Scrapy
• [ ] Databases:
  • [ ] SQL :
    • [ ] MYSQL
    • [ ] PostgreSQL
  • [ ] NOSQL :
    • [ ] MongoDB
• [ ] EDA :
  • [ ] Mark Keith : EDA in Depth
  • [ ] TowardsDataScience EDA Guide
  • [ ] Medium Intro to EDA
  • [ ] Medium Data Cleaning & EDA
  • [ ] TowardsDataScience Extensive EDA Guide
  • [ ] Medium How to ace EDA
  • [ ] AnalyticsVidhya EDA
• [ ] Data Preprocessing :
  • [ ] Preprocessing Overview & Imp Concepts
    • [ ] Neptune AI Blog : Data Preprocessing Guide
    • [ ] Serokello Blog about Data Preprocessing
    • [ ] TowardsDataScience.com Data Preprocessing Concepts
    • [ ] Analyticsvidhya Data-preprocessing Guide
  • [ ] Feature Engineering
    • [ ] Kaggle Feature Eng. Course
    • [ ] KDNuggets Feature Eng.
    • [ ] TowardsDataScience Feature Eng.
    • [ ] MachineLearningMastery Feature Eng.
    • [ ] AnalyticsVidhya Feature Eng.
  • [ ] Feature Selection
    • [ ] KDNuggets Feature Selection Overview
    • [ ] MachineLearningMastery Feature Selection
    • [ ] AnalyticsVidhya Feature Selection Techniques
    • [ ] MachineLearningPlus Feature Selection

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 :
  • [ ] Flask WebApp & API
  • [ ] Fast API
  • [ ] Streamlit

Final Projects

• [ ] House Prices - Advanced Regression Techniques
• [ ] Titanic - Machine Learning from Disaster

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
9. Scaler Blog

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