tensorflowonspark 2.2.5

Horovod is a powerful distributed training framework for Python that allows you to train deep learning models across multiple GPUs and servers quickly and efficiently. It falls under the category of distributed computing libraries. Built on top of TensorFlow, PyTorch, and other popular deep learning frameworks, Horovod simplifies the process of scaling up your model training by handling the complexities of distributed training under the hood.

Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark

Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark

Sparkling Water integrates H2O's Fast Scalable Machine Learning with Spark

PyOptimus is a Python library that brings together the power of various data processing engines like Pandas, Dask, cuDF, Dask-cuDF, Vaex, and PySpark under a single, easy-to-use API. It offers over 100 functions for data cleaning and processing, including handling strings, processing dates, URLs, and emails. PyOptimus also provides out-of-the-box functions for data exploration and quality fixing. One of the key features of PyOptimus is its ability to handle large datasets efficiently, allowing you to use the same code to process data on your laptop or on a remote cluster of GPUs.

John Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.

Flower: A Friendly Federated Learning Framework

Web app for https://github.com/labmlai/labml

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.