Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

Overview

Think Bayes 2

by Allen B. Downey

The HTML version of this book is here.

Think Bayes is an introduction to Bayesian statistics using computational methods.

Think Bayes is a Free Book. It is available under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), which means that you are free to copy and modify it, as long as you attribute the work and don’t use it for commercial purposes.

Other Free Books by Allen Downey are available from Green Tea Press.

Run the notebooks

Download the notebooks as a Zip file

Or use these links to run the notebooks on Colab:

Owner
Allen Downey
Professor at Olin College, author of Think Python, Think Bayes, Think Stats, and other books. Blog author of Probably Overthinking It.
Allen Downey
3D dataset of humans Manipulating Objects in-the-Wild (MOW)

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Leaderboard and Visualization for RLCard

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3D-Reconstruction 基于深度学习方法的单目多视图三维重建

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Compressed Video Action Recognition

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Link prediction using Multiple Order Local Information (MOLI)

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Implementation of our paper 'RESA: Recurrent Feature-Shift Aggregator for Lane Detection' in AAAI2021.

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September-Assistant - Open-source Windows Voice Assistant

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As-ViT: Auto-scaling Vision Transformers without Training

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LUKE -- Language Understanding with Knowledge-based Embeddings

LUKE (Language Understanding with Knowledge-based Embeddings) is a new pre-trained contextualized representation of words and entities based on transf

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Convert ONNX model graph to Keras model format.

Convert ONNX model graph to Keras model format.

Grigory Malivenko 175 Dec 28, 2022
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions"

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Pytorch implementation of Hinton's Dynamic Routing Between Capsules

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Space robot - (Course Project) Using the space robot to capture the target satellite that is disabled and spinning, then stabilize and fix it up

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