Repository Index

🤗 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

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

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

Convert Machine Learning Code Between Frameworks

• python
• tensorflow
• pytorch
• numpy

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

• deep-learning
• deeplearning
• deep
• learning

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

• machine-learning
• experiment-track
• deep-learning
• keras

Fast and Accurate ML in 3 Lines of Code

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

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

• pytorch
• tensorboard
• machine-learning
• visualization

Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.

• python
• ai
• data-science
• data-visualization

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

• cntk
• visualization
• tensorflow
• model-converter

ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.

• mlops
• machine-learning
• data-science
• production-ready

Scalable and user friendly neural :brain: forecasting algorithms.

• deep-learning
• forecasting
• esrnn
• nbeats

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

• machine-learning
• ml
• model-validation
• data-validation

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

• python
• genetic-algorithm
• optimization
• numpy

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

• deep-learning
• protein-sequences
• protein-structure
• semi-supervised-learning

Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

• pandas
• pandas-summary
• dataframes
• data-science

Code for PaperRobot: Incremental Draft Generation of Scientific Ideas

• pytorch
• memory-networks
• generation
• end-to-end-learning

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

• deep-learning
• agriculture
• pytorch
• dataset

Deep and Machine Learning for Microscopy

• microscopy
• materials
• machine-learning
• materials-science

MCP server for spatial transcriptomics analysis through natural language interfaces.

• bioinformatics
• cell-communication
• deconvolution
• machine-learning