While crystal balls are notoriously unreliable, lately there has been a lot of interesting work around the planning and development of Apache Spark 3.0. In t...

This is a paper in a “Seminal Papers in ML” series by MIT Machine Intelligence Community (MIC). MIT MIC aims to educate the community…

Hear from Andrej Karpathy on how Tesla is using PyTorch to develop full self-driving capabilities for its vehicles, including AutoPilot and Smart Summon.

When we look very closely at images generated by neural networks, we often see a strange checkerboard pattern of artifacts.

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The mentioned #OpenAI blog post on the gradients and its notebook are available here:
Post: https://www.wandb.com/articles/exploring-gradients
Notebook: https:/…

Speaker: Yikang Shen

Paper: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

Authors: Yikang Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville

In general, natural language is governed by a tree structure: smaller units (e.g.…

LSTM's and GRU's are widely used in state of the art deep learning models. For those just getting into machine learning and deep learning, this is a guide in plain English with helpful visuals to help you grok LSTM's and GRU's.

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Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

A friendly explanation of how computers predict and generate sequences, based on Recurrent Neural Networks.
For a brush up on Neural Networks…

Backpropagation through time
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Best Books on Machine Learning :
1. Introduction to…

When we look very closely at images generated by neural networks, we often see a strange checkerboard pattern of artifacts.

Part of the End-to-End Machine Learning School Course 193, How Neural Networks Work at https://e2eml.school/193

A lot of our code is in the process of being transitioned from Software 1.0 (code written by humans) to Software 2.0 (code written by an optimization, commonly in the form of neural network training). In the new paradigm, much of the attention of a developer…

GPU benchmarks for training State of the Art (SOTA) deep learning models. We measure each GPU's performance by batch capacity and more.