Q-learning for beginners

The goal of this article is to teach an AI how to solve the ❄️Frozen Lake environment using reinforcement learning. We’re going to start from scratch and try to recreate the Q-learning algorithm by ourselves. We’ll not just understand how it works, but more importantly, why it was designed that way. By the end of this article, you’ll master the Q-learning algorithm and be able to apply it to other environments. It’s a cool mini-project that gives a better insight […]

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Avalanche RL: an End-to-End Library for Continual Reinforcement Learning

Avalanche RL is a fork of ContinualAI’s Pytorch-based framework Avalanche with the goal of extending its capabilities to Continual Reinforcement Learning (CRL), bootstrapping from the work done on Super/Unsupervised Continual Learning. It should support all environments sharing the gym.Env interface, handle stream of experiences, provide strategies for RL algorithms and enable fast prototyping through an extremely flexible and customizable API. The core structure and design principles of Avalanche are to remain untouched to easen the learning curve for all continual […]

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Solutions of Reinforcement Learning 2nd Edition

How to contribute and current situation (9/11/2021~) I have been working as a full-time AI engineer and barely have free time to manage this project any more. I want to make a simple guidance of how to response to contributions: For exercises that have no answer yet, (for example, chapter 12) Prepare your latex code, make sure it works and looks somewhat nice. Send you code to [email protected]. By default, I will put contributer’s name in the pdf file, besides […]

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A Review of 2020 and Trends in 2021 – A Technical Overview of Machine Learning and Deep Learning!

Introduction Data science is not a choice anymore. It is a necessity. 2020 is almost in the books now. What a crazy year from whichever standpoint you look at it. A pandemic raged around the world and yet it failed to dim the light on data science. The thirst to learn more continued unabated in our community and we saw some incredible developments and breakthroughs this year. From OpenAI’s mind-boggling GPT-3 framework to Facebook’s DETR model, this was a year […]

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Top 5 Machine Learning GitHub Repositories & Reddit Discussions (October 2018)

Introduction “Should I use GitHub for my projects?” – I’m often asked this question by aspiring data scientists. There’s only one answer to this – “Absolutely!”. GitHub is an invaluable platform for data scientists looking to stand out from the crowd. It’s an online resume for displaying your code to recruiters and other fellow professionals. The fact that GitHub hosts open-source projects from the top tech behemoths like Google, Facebook, IBM, NVIDIA, etc. is what adds to the gloss of […]

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2019 In-Review and Trends for 2020 – A Technical Overview of Machine Learning and Deep Learning!

Overview A comprehensive look at the top machine learning highlights from 2019, including an exhaustive dive into NLP frameworks Check out the machine learning trends in 2020 – and hear from top experts like Sudalai Rajkumar and Dat Tran!   Introduction 2020 is almost upon us! It’s time to welcome the new year with a splash of machine learning sprinkled into our brand new resolutions. Machine learning will continue to be at the heart of what we do and how […]

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11 Superb Data Science Videos Every Data Scientist Must Watch

Overview Presenting 11 data science videos that will enhance and expand your current skillset We have categorized these videos into three fields – Natural Language Processing (NLP), Generative Models, and Reinforcement Learning Learn how the concepts in these videos work and build your own data science project!   Introduction I love learning and understanding data science concepts through videos. I simply do not have the time to pour through books and pages of text to understand different ideas and topics. […]

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