Index of Best AI/Machine Learning Resources

Index of AI ML Resources

Artificial Intelligence/Machine Learning field is is one of the most exciting fields in the world as of now and getting a great deal of consideration at the present time, and knowing where to begin can be somewhat troublesome.

I’ve been fiddling with this field, so I thought of curating the best AI/ML assets in one place. These are curated in light of if it’s a moving perused or a significant asset. I trust this curated list enable you to begin on what you have to think about AI/Machine Learning on a specialized level.

I have found some of very interesting and useful articles covering very basics to intermediate aspects of AI ,Machine Learning,Deep Learning,Python,Maths around the web.

 

Best FREE Courses on AI/ML/DL (Must See)

Machine Learning Crash courses from Berkeley Tutorial-1 Tutorial-2 Tutorial-3

Free AI Courses

Free Machine Learning Courses

Free Machine Learning online course (MOOC) over 4+ Million views

Free Machine Learning Course materials with Slides & Video Recordings: 2014-2015

Machine Learning Foundations: A Case Study Approach from Coursera

Neural Networks for Machine Learning from Coursera

Machine Learning from Standford

Coursera — Machine Learning (Andrew Ng)

Coursera — Neural Networks for Machine Learning (Geoffrey Hinton)

Udacity — Intro to Machine Learning (Sebastian Thrun)

Udacity — Machine Learning (Georgia Tech)

Udacity — Deep Learning (Vincent Vanhoucke)

Machine Learning (mathematicalmonk)

Practical Deep Learning For Coders (Jeremy Howard & Rachel Thomas)

Stanford CS231n — Convolutional Neural Networks for Visual Recognition (Winter 2016) (class link)

Stanford CS224n — Natural Language Processing with Deep Learning (Winter 2017) (class link)

Oxford Deep NLP 2017 (Phil Blunsom et al.)

Reinforcement Learning (David Silver)

Practical Machine Learning Tutorial with Python (sentdex)

 

Best Videos on AI/ML/DL (Must Watch)

Top 50 Recent AI Videos

Top Videos on ML

Top 10 Best Deep Learning Videos, Tutorials & Courses on Youtube from 2017

10 Free Training Courses on Machine Learning and Artificial Intelligence

Top 50 Recent Neural Networks Videos

Neural Network that Changes Everything – Computerphile

The Deep End of Deep Learning

MIT Introduction to Deep Learning and Self-Driving Cars

Andrew Ng: Artificial Intelligence is the New Electricity

Machine learning & art – Google I/O 2016

 

Best YouTube channels (FREE)

Machine Learning Recipes with Josh Gordon

sentdex

Siraj Raval

Two Minute Papers

DeepLearning.TV

Machine Learning at Berkeley

Artificial Intelligence — Topic

Understanding Machine Learning — Shai Ben-David

 

 

Best Tutorials on ML

gentle-guide-to-machine-learning

The world’s easiest introduction to Machine Learning (machine-learning-is-fun)

Machine Learning Tutorial with Examples

machine-learning-algorithm-use

 

 

Best Tutorials on Neural networks

Role of Bias in Neural Networks

Bias Nodes in Neural Networks

What is bias in artificial neural network?

Perceptrons 

The Perception

Single-layer Neural Networks (Perceptrons)

From Perceptrons to Deep Networks

 

Best Tutorials on Deep Learning

Deep Learning in a Nutshell

A Tutorial on Deep Learning

What is Deep Learning?

What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?

Deep Learning applied to NLP 

Deep Learning for NLP (without Magic)

Understanding Convolutional Neural Networks for NLP

Deep Learning, NLP, and Representations

Embed, encode, attend, predict: The new deep learning formula for state-of-the-art NLP models

Understanding Natural Language with Deep Neural Networks Using Torch

Deep Learning for NLP with Pytorch 

 

Best Tutorials on NLP

A Primer on Neural Network Models for Natural Language Processing 

The Definitive Guide to Natural Language Processing

Introduction to Natural Language Processing

Natural Language Processing Tutorial

Natural Language Processing (almost) from Scratch

Best Tutorials on Techniques of Machine Learning Process:

Support Vector Machines

An introduction to Support Vector Machines (SVM)

Support Vector Machines

Linear classification: Support Vector Machine, Softmax

 

Gradient Descent

Learning with gradient descent

Gradient Descent

How to understand Gradient Descent algorithm

An overview of gradient descent optimization algorithms

Optimization: Stochastic Gradient Descent

Regression

Introduction to linear regression analysis

Linear Regression

Linear Regression

Logistic Regression

Simple Linear Regression Tutorial for Machine Learning

Logistic Regression Tutorial for Machine Learning

Softmax Regression 

 

Backpropagation

Yes you should understand backprop

Can you give a visual explanation for the back propagation algorithm for neural networks?

How the backpropagation algorithm works

Backpropagation Through Time and Vanishing Gradients

A Gentle Introduction to Backpropagation Through Time

Backpropagation, Intuitions

 

Optimization and Dimensionality Reduction

Seven Techniques for Data Dimensionality Reduction

Principal components analysis

Dropout: A simple way to improve neural networks

How to train your Deep Neural Network

 

Long Short Term Memory (LSTM)

A Gentle Introduction to Long Short-Term Memory Networks by the Experts

Understanding LSTM Networks

Exploring LSTMs

Anyone Can Learn To Code an LSTM-RNN in Python

 

Convolutional Neural Networks (CNNs)

Introducing convolutional networks

Deep Learning and Convolutional Neural Networks

Conv Nets: A Modular Perspective

Understanding Convolutions

 

Recurrent Neural Nets (RNNs)

Recurrent Neural Networks Tutorial

Attention and Augmented Recurrent Neural Networks

The Unreasonable Effectiveness of Recurrent Neural Networks

A Deep Dive into Recurrent Neural Nets

 

Reinforcement Learning

Simple Beginner’s guide to Reinforcement Learning & its implementation

A Tutorial for Reinforcement Learning

Learning Reinforcement Learning

Deep Reinforcement Learning: Pong from Pixels

 

Generative Adversarial Networks (GANs)

What’s a Generative Adversarial Network?

Abusing Generative Adversarial Networks to Make 8-bit Pixel Art

An introduction to Generative Adversarial Networks (with code in TensorFlow)

Generative Adversarial Networks for Beginners

 

Word Vectors

Bag of Words Meets Bags of Popcorn

On word embeddings Part IPart IIPart III

The amazing power of word vectors

word2vec Parameter Learning Explained

Word2Vec Tutorial — The Skip-Gram ModelNegative Sampling

 

Encoder-Decoder

Attention and Memory in Deep Learning and NLP

Sequence to Sequence Models

Sequence to Sequence Learning with Neural Networks

Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences

How to use an Encoder-Decoder LSTM to Echo Sequences of Random Integers

 

 

AI R&D Organizations

 

Google Research

AWS AI

Facebook AI Research

OpenAI

DeepMind

Microsoft Research

Baidu Research

IntelAI

AI²

Partnership on AI

 

Python

A Complete Guide on Getting Started with Deep Learning in Python

7 Steps to Mastering Machine Learning With Python

An example machine learning notebook

How To Implement The Perceptron Algorithm From Scratch In Python

Implementing a Neural Network from Scratch in Python

A Neural Network in 11 lines of Python

Implementing Your Own k-Nearest Neighbour Algorithm Using Python

Demonstration of Memory with a Long Short-Term Memory Network in Python

How to Learn to Echo Random Integers with Long Short-Term Memory Recurrent Neural Networks

How to Learn to Add Numbers with seq2seq Recurrent Neural Networks

 

Scipy and numpy

Scipy Lecture Notes

Python Numpy Tutorial

An introduction to Numpy and Scipy

A Crash Course in Python for Scientists

 

scikit-learn

PyCon scikit-learn Tutorial Index

scikit-learn Classification Algorithms

scikit-learn Tutorials

Abridged scikit-learn Tutorials

 

PyTorch

PyTorch Tutorials

A Gentle Intro to PyTorch

Tutorial: Deep Learning in PyTorch

PyTorch Examples

PyTorch Tutorial

PyTorch Tutorial for Deep Learning Researchers

Tensorflow

Tensorflow Tutorials

learn-tensorflow-and-deep-learning-without-a-phd

Introduction to TensorFlow — CPU vs GPU

TensorFlow: A primer

RNNs in Tensorflow

Implementing a CNN for Text Classification in TensorFlow

How to Run Text Summarization with TensorFlow

 

Math

Math for Machine Learning

Math for Machine Learning-1

 

Linear algebra

An Intuitive Guide to Linear Algebra

A Programmer’s Intuition for Matrix Multiplication

Understanding the Cross Product

Understanding the Dot Product

Linear Algebra for Machine Learning

Linear algebra cheat sheet for deep learning

Linear Algebra Review and Reference

 

Probability

Understanding Bayes Theorem With Ratios

Review of Probability Theory (Stanford CS229)

Probability Theory Review for Machine Learning (Stanford CS229)

Probability Theory (U. of Buffalo CSE574)

Probability Theory for Machine Learning (U. of Toronto CSC411)

 

Calculus

How To Understand Derivatives: The Quotient Rule, Exponents, and Logarithms

How To Understand Derivatives: The Product, Power & Chain Rules

Vector Calculus: Understanding the Gradient

Differential Calculus

Calculus Overview

 

Miscellaneous

 15 Algorithms Machine Learning Engineers Must Need to Know

An Overview of Multi-Task Learning in Deep Neural Networks

Top & Best Artificial Intelligence Products/Companies

Best 2017 Artificial Intelligence Videos Playlist

A List of Free AI Software Programs to Download

Essential Cheat Sheets for Machine Learning Python and Maths

List of 10 Free Must-Read Books for Machine Learning

CONCLUSION

On the off chance that there are great instructional exercises you know about that I’m missing, please inform me!

I’m endeavoring to restrict only important instructional exercises since much past that would be tedious. Each weblink ought to have diverse material from alternate connections or present data in an unexpected way.

 

 

Related:

HOW TO LEARN MACHINE LEARNING IN 90 DAYS

6 Easy Steps To Get Started Learning Artificial Intelligence

 A Complete Guide on Getting Started with Deep Learning

Learn TensorFlow and deep learning, without a Ph.D.

15 algorithms machine learning engineers must need to know

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