Image augmentation library in Python for machine learning.
- augmentation
- machine-learning
- deep-learning
- neural-networks
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Image augmentation library in Python for machine learning.
A Python implementation of LightFM, a hybrid recommendation algorithm.
An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
Lightning ⚡️ fast forecasting with statistical and econometric models.
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
modular quant framework.
Scalable and user friendly neural :brain: forecasting algorithms.
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.
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
Fast Python Collaborative Filtering for Implicit Feedback Datasets
A python library for self-supervised learning and latent world models on images.
Fast, flexible and easy to use probabilistic modelling in Python.
Seamlessly integrate LLMs into scikit-learn.
Visual tracking library based on PyTorch.
PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.
Accelerated deep learning R&D
The machine learning toolkit for time series analysis in Python
Visualize and compare datasets, target values and associations, with one line of code.
:sunglasses: A curated list of robotics libraries and software
StellarGraph - Machine Learning on Graphs
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies