ML Review

Highlights from Machine Learning Research, Projects and Learning Materials. From and For ML Scientists, Engineers an Enthusiasts.

Editors
Machine Learning Digest

A hand-curated monthly round-up of credible papers, books, videos and software related to Machine Learning: https://mlreview.com.

ML Review Team

A hand-curated weekly round-up of credible papers, books, videos and software related to Machine Learning. https://twitter.com/ml_review

Latest Posts

The Intuition behind Adversarial Attacks on Neural Networks

Are the machine learning models we use intrinsically flawed?

Mastering Fast Gradient Boosting on Google Colaboratory with free GPU

Learn how to easily and quickly train Gradient Boosted Decision Trees on a GPU.

AI Distillery (Part 2): Distilling by Embedding

Word embeddings (word2vec, fastText), paper embeddings (LSA, doc2vec), embedding visualisation, paper search and charts!

Understanding building blocks of ULMFIT

Last week I had the time to tackle a Kaggle NLP competition: Quora Insincere Questions Classification. As it’s easy to understand from the…

AI Distillery (Part 1): A bird’s eye view of AI research

Different lenses to see through AI; motivations and introduction to our web app

Simple guide to Neural Arithmetic Logic Units (NALU): Explanation, Intuition and Code

The research engineers at DeepMind including well known AI researcher and author of the book Grokking Deep Learning, Andrew Trask have…

Multi-Modal Methods: Image Captioning (From Translation to Attention)

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two)

Helping AI Uncover the Mysterious Veil of Chinese Characters

This article is part of the Academic Alibaba series and is taken from the paper entitled “Learning Chinese Word Embeddings with Stroke…

Multi-Modal Methods: Visual Speech Recognition (Lip Reading)

Recent Intersections Between Computer Vision and Natural Language Processing (Part One)

Making Sense of the Bias / Variance Trade-off in (Deep) Reinforcement Learning

What goes into a stable, accurate reinforcement signal?

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