andresveraf

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

Auto-GPT

An experimental open-source attempt to make GPT-4 fully autonomous.

best-of-ml-python

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

cs-video-courses

List of Computer Science courses with video lectures.

Generative-AI-with-LLMs

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

INFO257

Inteligencia Artificial 2020, Ingeniería Civil Informática, Universidad Austral de Chile

LangChain-Chat-with-Your-Data

Start building practical applications that allow you to interact with data using LangChain and LLMs.

ml_guides

PyTorch_Notes

My Notes on A Series of PyTorch Lectures

sentence-transformers

Multilingual Sentence & Image Embeddings with BERT

andresveraf/Bitcoin-NLP-Strategy

A project attempting to create a profitable investment strategy for Bitcoin based on CatBoost and NLP with social media data.

andresveraf/PyTorch_Notes

My Notes on A Series of PyTorch Lectures

andresveraf/courses_notebooks

Jupyter notebooks for the EL4106 "Computational Intelligence" and AS4501 "Astroinformatics" courses at Universidad de Chile

andresveraf/Crypto-Twitter-Analysis

andresveraf/Deep-Learning-in-Production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

andresveraf/Diffusion-Probabilistic-Models

Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics

andresveraf/fastai-notes

Notes on the fast.ai ML Lectures

andresveraf/feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

andresveraf/LightGBM

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

andresveraf/Machine-Learning-Foundations

In progress: Jupyter Notebook on the Mathematical Foundation of Machine Learning

andresveraf/Sequence-Classification-with-LSTM

andresveraf/TensorFlow-Tutorials

Simple tutorials using Google's TensorFlow Framework