Semantic Image Segmentation in Pytorch
A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications
A Python library for machine learning on graph-structured (or equivalently, network-structured) data.
A cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers
A Crazy Fast, Super-Scalable, Flexibly Consistent KVS
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
A library for efficient similarity search and clustering of dense vectors.
A platform that helps you build, manage and monitor deep learning models
A Real-Time Multi-Person Keypoint Detection And Multi-Threading C++ Library
A Golang library for text processing, including tokenization, part-of-speech tagging, and named-entity extraction.
Use the world of Python from the comfort of Scala!
Model summary in PyTorch similar to 'model.summary()' in Keras
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Module for automatic summarization of text documents and HTML pages.
Python Library for Model Agnostic Interpretation
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
A Python-embedded modeling language for convex optimization problems.
A computer algebra system written in pure Python
A fast, ergonomic and portable tensor library in Nim with a deep learning focus
Mycroft Core, the Mycroft Artificial Intelligence platform.
Multi-dimensional arrays with broadcasting and lazy computing
A library to efficiently train Deep Learning models in a homomorphically encrypted state
A python library for automated feature engineering
Python factor analysis library (PCA, CA, MCA, FAMD)
A mobile-optimized implementation of quantized neural network operators