Simulation code and accompanying material for the textbook "Introduction to Multiple Antenna Communications and Reconfigurable Surfaces" by Emil Björnson and Özlem Tuğfe Demir, Boston-Delft: now pu…

Collection of notebooks for time series analysis

Awesome-LLM: a curated list of Large Language Model

Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

Understanding Deep Learning - Simon J.D. Prince

Scalable and user friendly neural 🧠 forecasting algorithms.

A flexible, intuitive and fast forecasting library

pymgrid is a python library to generate and simulate a large number of microgrids.

MAMBA – Multi-pAradigM voxel-Based Analysis: a computational cookbot

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

Paper list of multi-agent reinforcement learning (MARL)

A collection of open datasets for industrial applications, divided by categories

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbin…

A python library for user-friendly forecasting and anomaly detection on time series.

A curated list of references for MLOps

This repository contains implementations and illustrative code to accompany DeepMind publications

Code / solutions for Mathematics for Machine Learning (MML Book)

Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Machine Learning Conference & Summer School Notes. 🦄

An ongoing list of pandas quirks

Data and code for the article "The intrinsic predictability of ecological time series and its potential to guide forecasting"

My Own Solution Manual of PRML

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

Analisi dati del COVID 19 in Italia