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Deep Learning with Java

( Duration: 5 Days )

The Deep Learning with Java training course teaches to perform deep learning effectively, by leveraging the power of Java. You will learn to use DeepLearning4J, the popular Java library for deep learning, to a range of real-world use cases. They will then be introduced to Neural networks and how to implement them. You will also be given an insight about various deep learning algorithms and how to implement them for a variety of different data sets.

By attending Deep Learning with Java Workshop, delegates will learn to:

  • Get a practical deep dive into machine learning and deep learning algorithms
  • Implement machine learning algorithms related to deep learning
  • Explore neural networks using some of the most popular Deep Learning frameworks
  • Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms
  • Discover more deep learning algorithms with Dropout and Convolutional Neural Networks
  • Gain an insight into the deep learning library DL4J and its practical uses

This course is perfect for data scientists and machine learning developers/engineers who want to dive into the exciting world of deep learning. A fundamental knowledge of machine learning and knowledge of Java programming is all you need to get started with this course.



Deep Learning Overview


Preparing for Deep Learning


Deep Learning Libraries


Implementing neural networks


Practical Applications of Deep Learning


Fine-tuning your deep learning model

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

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Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.