A curated list of awesome Machine Learning frameworks, libraries and software.
A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by
If you want to contribute to this list (please do), send me a pull request or contact me @josephmisiti. Also, a listed repository should be deprecated if:
For a list of free machine learning books available for download, go here.
For a list of professional machine learning events, go here.
For a list of (mostly) free machine learning courses available online, go here.
For a list of blogs and newsletters on data science and machine learning, go here.
For a list of free-to-attend meetups and local events, go here.
ONNXruntime written in pure C (99) with zero dependencies focused on small embedded devices. Run inference on your machine learning models no matter which framework you train it with. Easy to install and compiles everywhere, even in very old devices.
illinois-core-utilitieswhich provides a set of NLP-friendly data structures and a number of NLP-related utilities that support writing NLP applications, running experiments, etc,
illinois-edisona library for feature extraction from illinois-core-utilities data structures and many other packages.
AInamespace. For instance, you can find Naïve Bayes.
Neuron - Neuron is simple class for time series predictions. It's utilize LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neural networks learned with Gradient descent or LeLevenberg–Marquardt algorithm.
NeuralTalk - NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences. [Deprecated]
Neuron - Neuron is simple class for time series predictions. It's utilize LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neural networks learned with Gradient descent or LeLevenberg–Marquardt algorithm. [Deprecated]
Data Driven Code - Very simple implementation of neural networks for dummies in python without using any libraries, with detailed comments.
Machine Learning, Data Science and Deep Learning with Python - LiveVideo course that covers machine learning, Tensorflow, artificial intelligence, and neural networks.
TResNet: High Performance GPU-Dedicated Architecture - TResNet models were designed and optimized to give the best speed-accuracy tradeoff out there on GPUs.
TResNet: Simple and powerful neural network library for python - Variety of supported types of Artificial Neural Network and learning algorithms.
Jina AI An easier way to build neural search in the cloud. Compatible with Jupyter Notebooks.
sequitur PyTorch library for creating and training sequence autoencoders in just two lines of code