List of Data Science and Machine Learning Resource that I frequently use
- R Cookbook
- R Blogdown
- ggplot2
- Headley Wickham
- Advance R
- R Package Documentation
- Parallel Processing in R
- Geo Computation with R
- Learn Python Org
- Python Graph Gallery
- Advanced Pandas Tricks & Techniques
- Collection of Jupyter Notebooks
- Streamlit library for ML visuals
- 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
- Flowing Data
- Seaborn pair plots
- D3 js examples
- D3 js examples newer version
- Data Visualization Society
- A Comprehensive guide to data exploration
- Dash
- Google AI Blog
- kdnuggets
- Kaggle
- Math Works
- In depth introduction to machine learning - Hastie & Tibshirani
- CS 229 ― Machine Learning
- UC Business Analytics R programming guide
- Machine Learning from CMU
- ML Cheatsheet - Stanford CS229
- Learning from Data
- The Learning Machine
- Machine Learning Plus
- 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
- 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
- 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
- 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
- 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
- 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
- Green Tea Press
- Machine learning and Data Science Books
- Time Series Analysis using R
- Free programming ebooks
- Columbia University Applied Machine Learning by Andreas Muller
- 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
- Interactive git tutorial for beginners
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent
