Elizer Ponio Jr's starred repositories
pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Image-Classification-App-with-Custom-TensorFlow-Model
Learn how to code your own neural network in Python, then deploy it in an Image Classification App using TensorFlow Lite.
youtube-tutorials
Companion code for tutorials on the AssemblyAI YouTube channel
bigdataengineering
Educational material for big data engineering courses
sec-insights
A real world full-stack application using LlamaIndex
llama_index_starter_pack
This repository provides very basic flask, streamlit, and docker examples for the llama_index (fka gpt_index) package
Modern-Computer-Architecture-and-Organization
Modern Computer Architecture and Organization, published by Packt
llama_index
LlamaIndex is a data framework for your LLM applications
Machine-Learning-From-Scratch
Implementation of popular ML algorithms from scratch
Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
alpaca-lora
Instruct-tune LLaMA on consumer hardware
self-instruct
Aligning pretrained language models with instruction data generated by themselves.
doing_data_science
This is the example code repository for Doing Data Science by Cathy O'Neil and Rachel Schutt (O'Reilly Media)
Tkinter-Designer
An easy and fast way to create a Python GUI 🐍
llama-recipes
Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment. Demo apps to showcase Meta Llama3 for WhatsApp & Messenger.
stablediffusion
High-Resolution Image Synthesis with Latent Diffusion Models
handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.