Orbax is a namespace providing common utility libraries for JAX users. Orbax also includes a serialization library for JAX users, enabling the exporting of JAX models to the TensorFlow SavedModel format.

Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16. It abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16 and leaves the rest of your code unchanged.

This package provides a Python library for outlier and anomaly detection, integrating classical and deep learning techniques .

This package groups functions to fetch datasets from several sources, converting them to scikit-learn compatible datasets.

This is a minimum version for checking the input argument dict. It would examine argument's type, as well as keys and types of its sub-arguments. A special case called variant is also handled, where you can determine the items of a dict based the value of on one of its flag_name key.

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API. Thanks to our define-by-run API, the code written with Optuna enjoys high modularity, and the user of Optuna can dynamically construct the search spaces for the hyperparameters.

Haiku is a simple neural network library for JAX. It is developed by some of the authors of Sonnet, a neural network library for TensorFlow.

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation and providing a delightful developer experience.

Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized.

clusteval is a Python package for unsupervised cluster evaluation. Three evaluation methods, Silhouette, DBindex, and Derivative are implemented that can be used to evalute clusterings for four clustering methods agglomerative, kmeans, dbscan and hdbscan.

Datasets is a lightweight library providing access to major public datasets (image, audio, text, etc.), as well as enabling efficient data preparation for inspection and ML model evaluation and training.

This package provides a library for sending commands and receiving replies to and from a Redis server. It comes with a synchronous API, asynchronous API and reply parsing API. Only the binary-safe Redis protocol is supported.

PyDMD is a Python package designed for Dynamic Mode Decomposition (DMD), a data-driven method used for analyzing and extracting spatiotemporal coherent structures from time-varying datasets. It provides a comprehensive and user-friendly interface for performing DMD analysis, making it a valuable tool for researchers, engineers, and data scientists working in various fields.

PyTorch extension for handling deeply nested sequences of variable length.

sklearn-compat is a small Python package that help developer writing scikit-learn compatible estimators to support multiple scikit-learn versions.

This package provides a neural network library for PyTorch compatible with the scikit-learn API.

TensorStore is a C++ and Python software library designed for storage and manipulation of large multi-dimensional arrays that:

• Provides advanced, fully composable indexing operations and virtual views.

• Provides a uniform API for reading and writing multiple array formats, including zarr and N5.

• Natively supports multiple storage systems, such as local and network filesystems, Google Cloud Storage, Amazon S3-compatible object stores, HTTP servers, and in-memory storage.

• Offers an asynchronous API to enable high-throughput access even to high-latency remote storage.

• Supports read caching and transactions, with strong atomicity, isolation, consistency, and durability (ACID) guarantees.

• Supports safe, efficient access from multiple processes and machines via optimistic concurrency.

Geomstats is an open-source Python package for computations, statistics, and machine learning on nonlinear manifolds. Data from many application fields are elements of manifolds. For instance, the manifold of 3D rotations SO(3) naturally appears when performing statistical learning on articulated objects like the human spine or robotics arms. Likewise, shape spaces modeling biological shapes or other natural shapes are manifolds.

hgboost is a python package for hyperparameter optimization for xgboost, catboost and lightboost for both classification and regression tasks.

This package provides a set of custom transformers, metrics and models complementing scikit-learn, which results from a collaboration between multiple companies in the Netherlands.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute. These are the provided Ray AI libraries:

• Data: Scalable datasets for ML;

• Train: Distributed training;

• Tune: Scalable hyperparameter tuning;

• RLlib: Scalable reinforcement learning;

• Serve: Scalable and programmable serving.

Melissa is a file-avoiding, adaptive, fault-tolerant and elastic framework, to run large-scale sensitivity analysis or deep-surrogate training on supercomputers. This package builds the API used when instrumenting the clients.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the UFCx interface header.

FFCx is a compiler for finite element variational forms.

From a high-level description of the form in the UFL, it generates efficient low-level C code that can be used to assemble the corresponding discrete operator (tensor). In particular, a bilinear form may be assembled into a matrix and a linear form may be assembled into a vector.

This package provides the CLI and Python library.