Repository Index

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

• deep-learning
• deep-learning-tutorial
• pytorch
• gan

Bootstrap Kubernetes the hard way. No scripts.

PyTorch Tutorial for Deep Learning Researchers

• deep-learning
• pytorch-tutorial
• neural-networks
• pytorch

Best Practices on Recommendation Systems

• machine-learning
• recommender
• ranking
• deep-learning

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 model family and using them on various provider services

• ai
• finetuning
• langchain
• llama

Gitbook

• micropoor
• micro8
• penetration

A neural network that transforms a design mock-up into a static website.

• keras
• deep-learning
• seq2seq
• encoder-decoder

TranslatedMachine learning tutorials

• machine-learning
• neural-network
• tensorflow
• python

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

• deep-learning
• mit
• self-driving-cars
• deep-reinforcement-learning

TensorFlow Tutorials with YouTube Videos

• tensorflow
• deep-learning
• machine-learning
• reinforcement-learning

TensorFlow tutorials and best practices.

• tensorflow
• neural-network
• deep-learning
• machine-learning

This repository has examples of broken patterns in ASP.NET Core applications

Kubernetes application example tutorials

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks

• neural-network
• image-classification
• machine-learning
• caffe

Claude Code Guide - Setup, Commands, workflows, agents, skills & tips-n-tricks from beginner to power user!

• ai
• ai-agent
• ai-agent-tools
• claude

:earth_americas: Simple and ready-to-use tutorials for TensorFlow

• deep-learning
• neural-network
• tensorflow
• machine-learning

Examples and Tutorials of Event Sourcing in .NET

• event-sourcing
• cqrs
• dotnet-core
• example

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

• machine-learning
• deep-learning
• lstm
• human-activity-recognition

TensorFlow Tutorials

• tensorflow-tutorials
• convolutional-neural-networks
• recurrent-neural-networks

Implementing a Neural Network from Scratch

Drawing Bayesian networks, graphical models, tensors, technical frameworks, and illustrations in LaTeX.

• latex
• machine-learning

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

• seq2seq
• tensorflow
• tensorflow-tutorials
• python

Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano