machine learning

Resources for Machine Learning: From the basics to working models

Gaurav

Aug 12, 2018 • 2 min read

The textbook definition of Machine Learning goes something like this: a subset of Artificial Intelligence that uses statistical techniques to get computers to learn without being explicitly programmed. Simply put, Machine Learning is making computers learn like humans by training it.

Below you will find a pool of resources from cheatsheets to working models that will get you started in the field of ML.

Machine Learning Cheatsheets
https://www.rankred.com/machine-learning-cheat-sheets/

Top-down learning path: Machine Learning for Software Engineers
https://github.com/ZuzooVn/machine-learning-for-software-engineers

Tutorial for Andrej Karpathy’s CNN Course! Really comprehensive tutorial to start from scratch
http://cs231n.github.io/

Making neural nets uncool again
http://www.fast.ai

NLP using Torch
https://harvard-ml-courses.github.io/cs287-web/

Lip Reading – Cross Audio-Visual Recognition using 3D Convolutional Neural Networks
https://github.com/astorfi/lip-reading-deeplearning

Collection of Interactive Machine Learning Examples
http://tools.google.com/seedbank/

Glow: Better Reversible Generative Models
https://blog.openai.com/glow/

Neural Network based Startup Name Generator
https://www.kdnuggets.com/2018/04/neural-network-startup-name-generator.html

Neural Joke Generation
https://web.stanford.edu/class/cs224n/reports/2760332.pdf

Keras Models in the browser
https://transcranial.github.io/keras-js/#/

Font Meme Generator
https://fontmeme.com/text-generator/

Tensorflow.js
https://js.tensorflow.org

Build a DNA-personalized app
https://genomelink.io/developers/

Tensorflow Dev Summit 2018 keynote
https://www.youtube.com/watch?v=kSa3UObNS6o&feature=youtu.be

TensorFlowJS: Machine Learning In JavaScript
https://youtu.be/656l4IfhM10

Articles and Reading Resources:

Self-Study Machine Learning Projects
http://bit.ly/2IFA1YT

Project- Gun Detector (a custom object detector)
Teammate- Jyot Prakash Verma
Framework Used – Tensorflow
https://www.linkedin.com/feed/update/urn:li:activity:6409461318050508800

How a Beginner Used Small Projects To Get Started in Machine Learning and Compete on Kaggle
http://bit.ly/2IFnqFr

Why ML interfaces will be more like pets than machines « Pete Warden’s blog
bit.ly/2MgTX7A

Building Mobile Applications with TensorFlow – a free book
https://oreil.ly/2JGh7Cv

Fruit Decay detection
http://www.ijircce.com/upload/2016/august/150_fruittedection.pdf

Facial emotion recognition
https://medium.com/@rishiswethan.c.r/emotion-detection-using-facial-landmarks-and-deep-learning-b7f54fe551bf

WaveNet is being used to generate the Google Assistant voices for US English and Japanese across all platforms
https://deepmind.com/blog/wavenet-launches-google-assistant/

How to learn deep learning in 6 months
https://towardsdatascience.com/how-to-learn-deep-learning-in-6-months-e45e40ef7d48

Reading an Academic Paper — DL/ML/AI
https://blog.goodaudience.com/reading-an-academic-paper-dl-ml-ai-2fa02976a571