Data-Science-and-Machine-Learning-Resources

List of Data Science and Machine Learning Resource that I frequently use

Agentic AI & Agents

• Agentic Design Patterns
• The New SDLC with Vibe Coding
• Agent Tools & Interoperability
• Agent Skills
• Agent Security and Evaluation
• Spec Driven Production Grade Development in the Age of Vibe Coding
• Agent Skills - Productin Grade Engineering Workflows & Loop Engineering

Agentic Development

• Agentic ADLC

Harness Engineering

• Harness Guide
• Harness Engineering Course
• Practical Harness Engineering with Google Antigravity

Large Language Models (LLMs) & Generative AI

• Awesome LLM
• Hands on LLM Repo

Basic Resources & Transformers

• The Illustrated Transformer
• Transformer Explained
• Visual Guide to Transformer Neural Networks
• Understanding Large Language Models
• Transformer models: an introduction and catalog — 2023 Edition

Advanced concepts

• Fine-tuning LLMs

Research Papers

LLM Architectures

• Attention is all you need
• BERTL Pre-training of Deep Biirectional transformers for Language Understanding
• LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attension
• Paramter-Efficient Transfer Learning for NLP
• Distillation - step by step
• SQL-PaLM: IMPROVED LARGE LANGUAGE MODEL ADAPTATION FOR TEXT-TO-SQL
• Language Models are Few-Shot Learners
• FINETUNED LANGUAGE MODELS ARE ZERO-SHOT LEARNERS
• Large Language Models are Zero-Shot Reasoners
• Scaling Laws for Neural Language Models
• REACT: SYNERGIZING REASONING AND ACTING INLANGUAGE MODELS
• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Data Science

• Data Science Central
• Towards Data Science
• Analytics Vidhya
• Data Science 101
• Data Science News
• Data Science Plus
• Listen Data
• Data Science Specialization Course Notes
• Various Data Science Tutorials
• Probabilistic Programming & Bayesian Methods for Hackers
• Unofficial Google Data Science Blog
• Data Science Cheat Sheet

R

• R Cookbook
• R Blogdown
• ggplot2
• Headley Wickham
• Advance R
• R Package Documentation
• Parallel Processing in R
• Geo Computation with R

Python

• Learn Python Org
• Python Graph Gallery
• Collection of Jupyter Notebooks
• Streamlit library for ML visuals
• Python Machine learning Notebooks
• Automate Stuff with Python
• Python from NSA
• Awesome Python
• Awesome Python Github
• Comprehensice python cheatsheet
• Real Python
• Function Decorators

Machine Learning

• Google AI Blog
• kdnuggets
• Kaggle
• Math Works
• In depth introduction to machine learning - Hastie & Tibshirani
• UC Business Analytics R programming guide
• Machine Learning from CMU
• ML Cheatsheet - Stanford CS229
• Learning from Data
• The Learning Machine
• Machine Learning Plus
• Machine Learning Resources from Sebastian Raschka
• Machine Learning Notebooks
• Machine Learning for beginners
• Curated Machine Learning Resources
• Machine Learning Toolbox
• Rules of Machine Learning: Best Practices for ML Engineering from Google
• Machine Learning Crash Course
• Machine Learning Interviews
• Applied ML - Curated list of papers, articles, and blogs on data science & machine learning in production
• Best of Machine Learning - Python
• Machine Learning Glossary
• Awesome Machine Learning
• Explanable AI
• Fairness and Machine Learning
• Google Reseatch 2021: Themes and beyond
• Machine Learning Complete - Notebooks & demos
• Awesome AI: A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers

MLOps

• MLOps References - Curated list of MLOps resources
• Industrialization of ML Model
• Awesome MLOps

Statistics & Probability

• Seeing Theory
• Applied Modern Statistical Learning Techniques
• Probability Theory & Mathematical Statistics
• Probability Distributions Overview
• Applied Data Mining and Statistical Learning (PSU)
• Intro to Statistics - Distributions, Power, Sample size, Effective trial design and mixed effect models
• Statistics How To
• Probability Distributions in R
• Mathematical Challenges
• Statistics Basics & Inference

Linear Algebra

• Numerical Analysis
• Introduction fo Linear Algebra for Applied Machine Learnign with Python

Deep Learning

• Deep Learning Papers and read
• Convolutional Neural Network
• Convolutional Neural Network for Visual Recognition
• A simple introduction of ANN
• How backpropagation works
• UFLDL DeepLearning Tutorials
• Classification Results using Deep Learing
• VGGNet Architecture on Imagenet
• Deep Learning Book
• Andrej Karpathy
• Dive into Deep Learning
• Deep Learning Examples in PyTorch by Nvidia
• Deep Learning Examples in TensorFlow by Nvidia
• Curve Detectors
• Deep Learning Drizzle
• Full Stack Deep Learning - training machine learning models to deploying AI systems in the real world
• Practical Deep Learning by Fasi.ai
• Transformers from Scratch

Time Series

• Forecasting Principles and Practice
• How To Identify Patterns in Time Series Data
• Applied Time Series Characteristics
• CausalImpact using Baysian structure time series
• Time Series Notes (Oregon State University)
• Extracting Seasonality and Trend from Data: Decomposition using R

Data Visualization

• Flowing Data
• Seaborn pair plots
• D3 js examples
• D3 js examples newer version
• Data Visualization Society
• A Comprehensive guide to data exploration
• Dash

ML Algorithms

• Regression (Glm)
• Forecasting using Time Series
• Types of Regressions
• Practice Algorithms
• Hidden Markov Models
• HMM Example: Dishonest Casino
• Hidden Markov Model Notes
• Kernals Trick(SVM)
• Boosting

Big Data

• Big Data - Cognitive AI
• Hadoop Ecosystem Table

Tech Blogs

• Open AI Blog
• Netflix Tech Blog for Data Science
• Google AI Blog
• Gogole DeepMind
• AirBnb Engineering & Data Science
• Facebook Research
• Meta AI
• The Yhat Blog
• Uber Engineering
• AWS Machine Learning
• Microsoft AI
• Open AI
• Uber Engineering
• Linkedin AI
• XAI
• NVIDIA AI
• Databricks Data Science & Machine Learning
• Spotify Engineering Blog
• Github AI & ML
• Chris Albon
• DS Lore
• Zack Stewart
• David Robinson
• Simply Statistics
• Citizen Statistics
• Civil Statistian
• R Studio Blog
• Data Science Plus
• R Weekly Org
• Andrew Gelman
• Edwin Chen's Blog
• R Statistcis co
• Datacamp Community News
• Data Science and Robots - Brandon Rohrer
• Lavanya.ai
• Data Flair
• Fast.ai Blog
• Domino Blog for Code, ML and Data Science
• Data36
• AI Show
• Distill.pub
• Jay Alammar - Blog on NLP and Deep Learning

Academia ML Courses

• CS 229 ― Machine Learning
• Stat202 - Data Mining and analysis
• Columbia University Applied Machine Learning by Andreas Muller

Public Datasets

• Fig Share
• Quandl
• Quora
• Public Data Sources
• US Gov
• Our World Data
• UCI Machine Learning Repository
• KDNuggets datasets
• Jerry Smith - Data Science Insights
• Data Quest
• Amazon Product Data
• Sentiment Analysis Datasets
• Machine Learning A-Z: Download Practice Datasets
• Microsoft Research Open Data
• Data Hub
• Collection of NLP datasets
• John Snow Labs NLP & Healthcare datasets
• Open Source Audio datasets

Videos on Data

• Ted Talks - Making sense of too much data
• Andrew Ng's ML Lectures - Stanford

Free Ebooks

• Green Tea Press
• Machine learning and Data Science Books
• Time Series Analysis using R
• Free programming ebooks
• Machine Learning
• 65 Free machine learnign and data books
• Free Programming and ML pdf books
• Approaching any machine learning problem

Misc

• Machine Learning Cheat Sheet in R
• Which algorithn should one use?
• Papers with code
• Browse State of the art
• Data Science Projects
• Churn Prediction & Survival Analysis
• Stanford Machine Learning Projects
• Amazon Science Reasearch and blog
• Machine Learning Questions
• Graph database for beginners
• Top Github Repos

Jupyter Notebooks

• Survival Regression with Sci-kit learn
• Evaluating Survival Regression
• Jupyter Notebook by Domain
• Jupyter Notebooks - DS,ML,TF,AWS,Python

Data Science Interview Prep

• Data Science Interview Questions - Springboard
• Data Science Interviews by Category
• 120 Data Science Interview Questions
• Facebook Interview Prep
• Software/ML Engineer Interview Prep
• Tech Interview Handbook
• DS Interview Questions-Answers
• Interview Query
• Machine Learning Interview

AI Engineer Interview Prep

• Awesoem AI Architect
• AI Engineering Interview Questions
• System Design Primer
• LLM Engineer Toolkit

Podcasts

• Dataframed by Datacamp
• Data Skeptic by Kyle Polich
• Linear Diagressions
• Gradient Dissent

Data Structure & Algorithms

• Geeks for Geeks
• Program Creek
• Career Cup
• A Gentle Introduction to Algorithm Complexity Analysis
• Always be Coding
• Competitive Programming Tutorials
• Python for Algorithms & Data Structure - Interview
• Skilled.dev
• Big O Cheatsheet
• The Algorithms Repo
• Interview Cake (Glossary)
• Algorithm & Coding Interviews
• SDE Skills
• Tech Interview Handbook

Interview Guide & Resources

• AI Engineering Learning Path
• SYSTEM DESIGN INTERVIEW- AN INSIDER'S GUIDE
• Grokking Teh System Design
• Awesome Scalability
• Microservice Demo

Git

• Git Explorer
• Interactive git tutorial for beginners
• How to Write a Git Commit Message
• Awesome Git
• Git Cheatsheet