Artificial Intelligence III - Deep Learning in Java

Deep Learning Fundamentals, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) + LSTM, GRUs

Ratings: 4.40 / 5.00




Description

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 - natural language processing and sentiment analysis!

So you'll learn about the following topics:

Section #1:

  • multi-layer neural networks and deep learning theory

  • activtion functions (ReLU and many more)

  • deep neural networks implementation

  • how to use deeplearning4j (DL4J)

Section #2:

  • convolutional neural networks (CNNs) theory and implementation

  • what are kernels (feature detectors)?

  • pooling layers and flattening layers

  • using convolutional neural networks (CNNs) for optical character recognition (OCR)

  • using convolutional neural networks (CNNs) for smile detection

  • emoji detector application from scratch

Section #3:

  • recurrent neural networks (RNNs) theory

  • using recurrent neural netoworks (RNNs) for natural language processing (NLP)

  • using recurrent neural networks (RNNs) for sentiment analysis

These are the topics we'll consider on a one by one basis.

You will get lifetime access to over 40+ lectures!

This course comes with a 30 day money back guarantee! If you are not satisfied in any way, you'll get your money back. Let's get started!

What You Will Learn!

  • Understands deep learning fundamentals
  • Understand convolutional neural networks (CNNs)
  • Implement convolutional neural networks with DL4J library in Java
  • Understand recurrent neural networks (RNNs)
  • Understand the word2vec approach

Who Should Attend!

  • Anyone who wants to understand deep learning, convolutional neural networks and recurrent neural networks in Java