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

Last update: Jan 08, 2023

Overview

Think Bayes 2

by Allen B. Downey

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.

GitHub Repository http://allendowney.github.io/ThinkBayes2/

Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.

Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline

12 Dec 02, 2022

Registration Loss Learning for Deep Probabilistic Point Set Registration

RLLReg This repository contains a Pytorch implementation of the point set registration method RLLReg. Details about the method can be found in the 3DV

35 Nov 02, 2022

Implementation of Graph Convolutional Networks in TensorFlow

Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n

6.6k Dec 30, 2022

This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.

RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models

5 Jan 04, 2023

Fantasy Points Prediction and Dream Team Formation

Fantasy-Points-Prediction-and-Dream-Team-Formation Collected Data from open source resources that have over 100 Parameters for predicting cricket play

2 Sep 13, 2022

BEGAN in PyTorch

BEGAN in PyTorch This project is still in progress. If you are looking for the working code, use BEGAN-tensorflow. Requirements Python 2.7 Pillow tqdm

260 Dec 07, 2022

for a paper about leveraging discourse markers for training new models

TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis

6 Nov 02, 2022

Introducing neural networks to predict stock prices

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

637 Jan 04, 2023

Code to compute permutation and drop-column importances in Python scikit-learn models

Feature importances for scikit-learn machine learning models By Terence Parr and Kerem Turgutlu. See Explained.ai for more stuff. The scikit-learn Ran

537 Dec 31, 2022

Notification Triggers for Python

Notipyer Notification triggers for Python Send async email notifications via Python. Get updates/crashlogs from your scripts with ease. Installation p

17 May 16, 2022

A new video text spotting framework with Transformer

TransVTSpotter: End-to-end Video Text Spotter with Transformer Introduction A Multilingual, Open World Video Text Dataset and End-to-end Video Text Sp

67 Jan 03, 2023

Automatic Differentiation Multipole Moment Molecular Forcefield

Automatic Differentiation Multipole Moment Molecular Forcefield Performance notes On a single gpu, using waterbox_31ang.pdb example from MPIDplugin wh

4 Jan 07, 2022

[NeurIPS 2021] PyTorch Code for Accelerating Robotic Reinforcement Learning with Parameterized Action Primitives

Robot Action Primitives (RAPS) This repository is the official implementation of Accelerating Robotic Reinforcement Learning via Parameterized Action

55 Dec 27, 2022

MOT-Tracking-by-Detection-Pipeline - For Tracking-by-Detection format MOT (Multi Object Tracking), is it a framework that separates Detection and Tracking processes?

MOT-Tracking-by-Detection-Pipeline Tracking-by-Detection形式のMOT(Multi Object Trac

41 Nov 23, 2022

Pytorch implementation for "Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets" (ECCV 2020 Spotlight)

Distribution-Balanced Loss [Paper] The implementation of our paper Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets (

304 Dec 22, 2022