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A cross-platform video structuring (video analysis) framework based on CV models & mLLM.

AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓，同时包含工作和科研过程中的新想法、新问题、新资源与新项目

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Learning to Rank in TensorFlow

Deep neural network to extract intelligent information from invoice documents.

[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"

Build, personalize and control your own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6

FMA: A Dataset For Music Analysis

A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun

Automatic architecture search and hyperparameter optimization for PyTorch

Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.

Machine learning metrics for distributed, scalable PyTorch applications.

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

SDG is a specialized framework designed to generate high-quality structured tabular data.

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

Graph Neural Networks with Keras and Tensorflow 2.

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Run Mixtral-8x7B models in Colab or consumer desktops

Source-to-Source Debuggable Derivatives in Pure Python

:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

An open source library and framework for deep learning on satellite and aerial imagery.

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Repository containing notebooks of my posts on Medium

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

Russian GPT3 models.

Interpretability and explainability of data and machine learning models

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Python AutoML for Trading Systems and Sports Betting