Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…

Code for Machine Learning for Algorithmic Trading, 2nd edition.

We are building an open database of COVID-19 cases with chest X-ray or CT images.

Machine Learning in Asset Management (by @firmai)

Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at

Various tutorials given for welcoming new students at MILA.

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

Tutorials on Causal Inference and pgmpy

Real NVP PyTorch a Minimal Working Example | Normalizing Flow

Gumbel-Softmax Variational Autoencoder with Keras

Material for the Montréal Deep Learning Summer School 2017

PyTorch implementation of "Conditional Image Generation with PixelCNN Decoders" by van den Oord et al. 2016

Personal Finance library for the Computationally Curious.

Repository for my studies of Causal Inference

Python package to interact with the PATRIC database (https://www.patricbrc.org)

⛷Monitor conditions at nearby ski hills using Dash from Plotly