Import Libraries Before we start building network, we need to import libraries #load the packages from io import open import os, string, random,...

Introduction The biggest issue facing machine learning is how to put the system into production. Machine learning systems differ from traditional software in two fundamental ways: Machine learning is never fully deterministic; therefore, the performance of an ML system can’t be evaluated against a strict specification. Instead, it should always be evaluated against application-specific metrics (false […]

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(Submitted on 29 Mar 2020) Abstract: We present Catalyst.RL, an open-source PyTorch framework for reproducible and sample efficient reinforcement learning (RL)...

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Transformers (specifically self-attention) have powered significant recent progress in NLP. They have enabled models like BERT, GPT-2, and XLNet to form powerful language...

Starsky Robotics shuts down, plus more news from world of neural networks Roundup Let's get cracking with some machine-learning news. Starksy Robotics is...

As we decided to create a list of inspiring people to follow in data science, we asked for help from the data...

Today, we are excited to announce that you can now use Amazon Elastic Inference to accelerate inference and reduce inference costs for PyTorch...

“What we want is a machine that can learn from experience“Alan Turing There is no doubt that Machine Learning has become...

Neural Magic claims algos in social network's open-source compiler on GitHub look awfully familiar An AI startup is suing Facebook and one of...

If you have to write an artificial intelligence (AI) or machine learning (ML) job description, it can be difficult to convey precisely what...

Rice University computer scientists have overcome a major obstacle in the burgeoning artificial intelligence industry by showing it is possible to speed up...