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Have good hands-on Apache Spark: Deep Learning Framework
- Explore the world of distributed deep learning with Apache Spark
- Train neural networks with deep learning libraries such as BigDL and TensorFlow
- Develop Spark deep learning applications to intelligently handle large and complex datasets
- Understand the basics of deep learning
- Set up Apache Spark for deep learning
- Understand the principles of distribution modeling and different types of neural networks
- Obtain an understanding of deep learning algorithms
- Discover textual analysis and deep learning with Spark
- Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras
- Explore popular deep learning algorithms
- Perform big data processing with Spark-without having to learn Scala!
- Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics
- Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark
- Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library.
- Perform analytics on data from various data sources such as Kafka, and Flume using Spark Streaming Library
- Learn SQL schema creation and the analysis of structured data using various SQL functions including Windowing functions in the Spark SQL Library
- Explore Spark Mlib APIs while implementing Machine Learning techniques to solve real-world problems
- Get to know Spark GraphX so you understand various graph-based analytics that can be performed with Spark