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Hama

Apache Hama is an open-source computing framework designed for massive-scale parallel computing tasks.

Introduction to Apache Hama

Get started with Apache Hama for massive-scale computation. Explore Bulk Synchronous Parallel (BSP) model, graph processing algorithms, and basic Hama ecosystem components.

Advanced Graph Processing with Apache Hama

Take your graph processing skills to the next level with Apache Hama. Explore Pregel model, graph partitioning strategies, and advanced algorithms for large-scale graph analytics with Hama.

Hama Cluster Administration

Learn Hama cluster administration for managing large-scale computation infrastructures. Explore cluster setup, monitoring, fault tolerance, and performance tuning with Hama.

Real-time Computation with Apache Hama

Learn real-time computation techniques with Apache Hama. Explore streaming processing models, event-driven architectures, and real-time analytics with Hama.

Scalable Machine Learning with Apache Hama

Learn scalable machine learning techniques with Apache Hama. Explore distributed machine learning algorithms, model training strategies, and large-scale data processing with Hama.

Advanced Apache Hama Programming

This advanced course delves deeper into Apache Hama programming techniques, focusing on optimization, performance tuning, and advanced features.?

Participants will gain insights into maximizing the efficiency of their Apache Hama applications.

Apache Hama for Machine Learning

This course focuses on using Apache Hama for distributed machine learning tasks. Participants will learn how to leverage Apache Hama's capabilities to build scalable and efficient machine learning models for various applications.

Introduction to Apache Hama

This course provides an introduction to Apache Hama, an open-source distributed computing framework for massive scientific computations such as matrix, graph, and network algorithms.?

Participants will gain an understanding of the fundamental concepts of Apache Hama and learn how to leverage its features to build scalable and efficient distributed computing applications.

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