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machinelearning-samples

Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.

maddpg

Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".

mcdo

A pytorch implementation of MCDO(Monte-Carlo Dropout methods)

ml-from-scratch

Machine Learning From Scratch. Bare bones Python implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.

mlrefined

Python and MATLAB code examples and demos from the textbook "Machine Learning Refined" (Cambridge University Press). See our blog https://jermwatt.github.io/mlrefined/index.html for interactive versions of many of the notebooks in this repo.

mmas-money-tracker

A free optimized application for daily expense tracking and finance management.

multi-agent-diverse-generative-adversarial-networks

Easy-to-follow Pytorch tutorial Notebook for Multi-Agent-Diverse-Generative-Adversarial-Networks

multivariate-time-series-data

multivariate-time-series-models-in-keras

This repository contains a throughout explanation on how to create different deep learning models in Keras for multivariate (tabular) time series prediction.

must-read-papers-for-ml

Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer

neural-networks

All about Neural Networks!

poppler-windows

Prebuilt Poppler binaries packaged for windows with dependencies

practical-time-series-analysis

Practical Time-Series Analysis published by Packt

probabilistic-backpropagation

Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.

prompt-engineering-guide

🐙 Guides, papers, lecture, notebooks and resources for prompt engineering

promptpapers

Must-read papers on prompt-based tuning for pre-trained language models.

pyldavis

Python library for interactive topic model visualization. Port of the R LDAvis package.

pytorch-rl

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

pytorch-seq2seq

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

q-trader

Deep Q-learning driven stock trader bot

random-forest-timeseries

Messing about with doing time series forecasting using Random Forest regression

react

[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models

react-clean-architecture

A realistic approach to implement clean architecture on react codebases

reinforcement-learning

Minimal and Clean Reinforcement Learning Examples

reinforcement-learning-1

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

rl-practice-keras

seq2seq-attn

Sequence-to-sequence model with LSTM encoder/decoders and attention

seq2seq-signal-prediction

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

seq2seqattn_ecm

(TensorFlow) Sequence to sequence with attention model, emotion regressor, and Emotional Chatting Machine.