Repository Index

All-in-one IoT Platform - Device management, data collection, processing and visualization.

• visualization
• iot
• iot-platform
• mqtt

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

• nlp
• datasets
• pytorch
• tensorflow

A High-Quality Real Time Upscaler for Anime Video

• anime
• upscaling
• upsampling
• video-processing

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

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

Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data.

• telegraf
• monitoring
• time-series
• metrics

QuestDB is a high performance, open-source, time-series database

• time-series
• low-latency
• database
• sql

📺 Discover the latest machine learning / AI courses on YouTube.

• machine-learning
• deep-learning
• nlp
• natural-language-processing

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

• pytorch
• python
• machine-learning
• deep-learning

pix2tex: Using a ViT to convert images of equations into LaTeX code.

• machine-learning
• transformer
• im2latex
• deep-learning

Topic Modelling for Humans

• gensim
• topic-modeling
• information-retrieval
• machine-learning

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report

• agent
• ai
• automation
• data-mining

Natural Language Processing Tutorial for Deep Learning Researchers

• nlp
• natural-language-processing
• tutorial
• pytorch

A curated list of awesome big data frameworks, ressources and other awesomeness.

• awesome
• bigdata
• data-warehouse
• data-analytics

Open3D: A Modern Library for 3D Data Processing

• mesh-processing
• computer-graphics
• opengl
• cpp

机器学习相关教程

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

Low-code framework for building custom LLMs, neural networks, and other AI models

• deep-learning
• deeplearning
• deep
• learning

PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.

• mupdf
• xps
• pdf-documents
• epub

Fast and Accurate ML in 3 Lines of Code

• automl
• machine-learning
• data-science
• deep-learning

Open source annotation tool for machine learning practitioners.

• natural-language-processing
• machine-learning
• annotation-tool
• python

YSDA course in Natural Language Processing

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

• pytorch
• speech-processing
• speaker-diarization
• speech-activity-detection

[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.

• data
• data-cleaning
• data-pipelines
• data-processing

🌊 Online machine learning in Python

• incremental-learning
• machine-learning
• python
• online-learning

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.