Stanza is a Python NLP Library for Many Human Languages. It contains support for running various accurate natural language processing tools on 60+ languages and for accessing the Java Stanford CoreNLP software from Python. A new collection of biomedical and clinical English model packages are now available, offering seamless experience for syntactic analysis and named entity recognition (NER) from biomedical literature text and clinical notes.

Stanza - A Python NLP Library for Many Human Languages

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, and tabular data.
 
<ul>
<li>Quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code.</li>
<li>Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge.</li>
<li>Leverage automatic hyperparameter tuning, model selection/ensembling, architecture search, and data processing.</li>
<li>Easily improve/tune your bespoke models and data pipelines, or customize <cite>AutoGluon</cite> for your use-case.</li>
</ul>

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, and tabular data.

AutoGluon - AutoML for Text, Image, and Tabular Data

Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.
 
Ray AI Runtime (AIR) is an open-source toolkit for building ML applications. It provides libraries for distributed data processing, model training, tuning, reinforcement learning, model serving, and more.
 
Ray Core provides a simple and flexible API for building and running your distributed applications. You can often parallelize single machine code with little to zero code changes.
 
With a Ray cluster you can deploy your workloads on AWS, GCP, Azure or on premise. You can also use Ray cluster managers to run Ray on your existing Kubernetes, YARN, or Slurm clusters.

Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.


Ray - A unified framework for scaling AI and Python applications

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more. 

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Stanza - A Python NLP Library for Many Human Languages

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Stanza - A Python NLP Library for Many Human Languages

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