Getting Started with Java Deep Learning
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VIDEO TUTORIAL Getting Started with Java Deep Learning

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Get the essential know-how on working with deep learning algorithms using Java.

About This Getting Started with Java Deep Learning Video course

  • Go beyond the theory and put deep learning into practice with Java
  • Work with powerful libraries to enhance your deep learning algorithms
  • Whether you’re a data scientist or Java developer, dive in and find out how to tackle deep learning

Java Deep Learning course In Detail

AI and deep learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. It is the technology behind self-driven cars, intelligent personal assistant computers, and decision support systems. Deep learning algorithms are being used across a broad range of industries. As the fundamental driver of AI, being able to tackle deep learning with Java is going to be a vital and valuable skill, not only within the tech world, but also for the wider global economy that depends upon knowledge and insight for growth and success.

You will learn how to install the environment, where Git is used as version control, Eclipse or IntelliJ as an IDE, and mostly Gradle with a little bit of Maven as a build tool. You will learn how to use the DL4J and apply deep learning to a range of real-world use cases. You will then be introduced to Neural networks and later you will learn how to implement them. You will also be given an insight about various deep learning algorithms. You will then be trained to tune Apache Spark.

By the end of the video course, you’ll be ready to tackle deep learning with Java. Wherever you’ve come from—whether you’re a data scientist or Java developer—you will become a part of the deep learning revolution!

What will you learn in this course?

Course plan
Chapter 1
Installation and Setup
Chapter 2
Neural Networks
Chapter 3
Implementing Neural Nets
Chapter 4
Deeper Architectures
Chapter 5

Detailed course plan

Chapter 1 : Installation and Setup
Lesson 1The Course Overview
Lesson 2Installing on Windows
Lesson 3Quick Start
Lesson 4Building NN Using GPU
Chapter 2 : Neural Networks
Lesson 1Classification and Clustering
Lesson 2Softmax Function
Lesson 3Multilinear Regression
Lesson 4Logistic Regression
Chapter 3 : Implementing Neural Nets
Lesson 1Gradient Descent
Lesson 2Multilayer Perceptron
Lesson 3Feed-Forward Neural Networks
Lesson 4Recurrent Neural Networks
Chapter 4 : Deeper Architectures
Lesson 1Long Short Term Memory Units
Lesson 2Convolutional Neural Networks
Lesson 3Denoising Autoencoders
Lesson 4Restricted Boltzmann Machine
Chapter 5 : Tuning
Lesson 1Hyper-Parameter Space
Lesson 2Fixing and Selecting Parameters
Lesson 3Early Stopping
Lesson 4Testing and Evaluating

Your questions about the course

With which software versions is this tutorial compliant ?

Java , Data Science

What is the required level to follow this tutorial ?


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