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This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Code for Machine Learning for Algorithmic Trading, 2nd edition.
Code release for NeRF (Neural Radiance Fields)
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Notebooks for learning deep learning
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
An educational AI robot based on NVIDIA Jetson Nano.
Quantitative research and educational materials
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Ipython notebooks for math and finance tutorials
Hands-On Reinforcement Learning with Python, published by Packt
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess finan…
Environment for reinforcement-learning algorithmic trading models
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading mar…
Transfer learning for music classification and regression tasks
Open source traditional chinese handwriting dataset.
This repository provides the code for a Reinforcement Learning trading agent with its trading environment that works with both simulated and historical market data. This was inspired by OpenAI Gym …
Generating automatic trimap through pixel dilation and strongly-connected-component algorithms
Implementation of Hierarchical Attention Networks in PyTorch
This repository contains a notebook demonstrating a practical implementation of the so-called Entity Embedding for Encoding Categorical Features for Training a Neural Network.