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Artificial Intelligence III - Deep Learning in Java


Artificial Intelligence III - Deep Learning in Java

Artificial Intelligence III - Deep Learning in Java Deep learning fundamentals, focusing on convolutional neural networks and recurrent neural networks, LTSM, GRUs

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What you'll learn

  • Understands deep learning fundamentals
  • Understand convolutional neural networks
  • Implement convolutional neural networks with DL4J library in Java


  • Some math (derivatives and matrix operations)
  • Java basics (classes, objects etc.)

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This course is about deep learning fundamentals and convolutional neural networks. Convolutional neural networks are one of the most successful deep learning approaches: self-driving cars rely heavily on this algorithm. First you will learn about densly connected neural networks and its problems. The next chapter are about convolutional neural networks: theory as well as implementation in Java with the deeplearning4j library. The last chapters are about recurrent neural networks and the applications!

So you'll learn about the following topics:

Section #1:

  • multi-layer neural networks and deep learning theory
  • deep neural networks implementation

Section #2:

  • Convolutional Neural Networks (CNNs) theory
  • using convolutional neural networks (CNNs) for optical character recognition (OCR)
  • emoji detector application from scratch

Section #3:

  • recurrent neural networks (RNNs) theory
  • using recurrent neural networks (RNNs) with sentiment analysis
  • These are the topics we'll consider on a one by one basis. Hope you will like it!

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