H2O is for data scientists and application developers who need fast, in-memory scalable machine learning for smarter applications. H2O is an open source parallel processing engine for machine learning. Unlike traditional analytics tools, H2O provides a combination of extraordinary math, a high performance parallel architecture, and unrivaled ease of use.
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H2O uses familiar interfaces like R, Python, Scala, the Flow notebook graphical interface, Excel, & JSON so that Big Data enthusiasts & experts can explore, munge, model, and score datasets using a range of algorithms including advanced ones like Deep Learning. H2O is extensible so that developers can add data transformations and model algorithms of their choice and access them through all of those clients.

H2O is for data scientists and application developers who need fast, in-memory scalable machine learning for smarter applications. H2O is an open source parallel processing engine for machine learning. Unlike traditional analytics tools, H2O provides a combination of extraordinary math, a high performance parallel architecture, and unrivaled ease of use.

H2O - Fast Scalable Machine Learning API For Smarter Applications

Deeplearning4J is an open source, distributed neural net library written in Java and Scala. It integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. It provides versatile n-dimensional array class for Java and Scala. 
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It is best suited for Face/image recognition, Voice search, Speech-to-text (transcription), Spam filtering (anomaly detection), Fraud detection, Recommender Systems (CRM, adtech, churn prevention), Regression.


Deeplearning4J is an open source, distributed neural net library written in Java and Scala. It integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. It provides versatile n-dimensional array class for Java and Scala. 

Deeplearning4J - Neural Net Platform in Java and Scala

RedisAI is a Redis module for executing Deep Learning/Machine Learning models and managing their data. Its purpose is being a "workhorse" for model serving, by providing out-of-the-box support for popular DL/ML frameworks and unparalleled performance. RedisAI both maximizes computation throughput and reduces latency by adhering to the principle of data locality , as well as simplifies the deployment and serving of graphs by leveraging on Redis' production-proven infrastructure.

RedisAI - A Redis module for serving tensors and executing deep learning graphs

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H2O - Fast Scalable Machine Learning API For Smarter Applications

Deeplearning4J - Neural Net Platform in Java and Scala

RedisAI - A Redis module for serving tensors and executing deep learning graphs

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H2O - Fast Scalable Machine Learning API For Smarter Applications

Deeplearning4J - Neural Net Platform in Java and Scala

RedisAI - A Redis module for serving tensors and executing deep learning graphs

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