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Deep Learning with Apache Spark Solutions

Implement practical hands-on examples with over 55 recipes that streamline Deep Learning with Apache Spark

     
  • 3.8
  •  |
  • Reviews ( 7 )
₹799

This Course Includes

  • iconudemy
  • icon3.8 (7 reviews )
  • icon3.5 total hours
  • iconenglish
  • iconOnline - Self Paced
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  • iconUdemy

About Deep Learning with Apache Spark Solutions

With Deep Learning gaining  rapid mainstream adoption in modern-day industries, organizations are  looking for ways to unite popular big data tools with highly efficient  Deep Learning libraries: TensorFlow and Keras which focuses on the pain  points of Convolution Neural Networks. As a result, you'll have the  expertise to train and deploy efficient Deep Learning models on Apache  Spark.

Packt’s Video Learning Paths are a series of individual video products  put together in a logical and stepwise manner such that each video  builds on the skills learned in the video before it.

This Course is a fast-paced guide to implementing practical hands-on  examples, streamlining Deep Learning with Apache Spark. You’ll begin  with understanding practical Machine Learning and Deep Learning concepts  to apply built-in Machine Learning libraries within Spark. Explore  libraries that are compatible with TensorFlow and Keras. You’ll create  and visualize word vectors using Word2vec, also create a movie  recommendation engine using Keras. Finally, you’ll implement practical  hands-on examples streamlining Deep Learning with Apache Spark  Solutions.

By the end of this course, you'll implement practical hands-on examples  with over 55 recipes that streamline Deep Learning with Apache Spark.

What You Will Learn?

  • Understand practical machine learning and deep learning concepts..
  • Apply built-in Machine Learning libraries within Spark..
  • Explore libraries that are compatible with TensorFlow and Keras..
  • Explore NLP models such as Word2vec and TF-IDF on Spark..
  • Face recognition using Deep Convolutional Networks..
  • Create and visualize word vectors using Word2vec..
  • Create a movie recommendation engine using Keras..
  • Manipulate and merge the MovieLens datasets..