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Getting Started with Java Deep Learning

COURSE
Packt Admin
3 hrs

Getting Started with Java Deep Learning

COURSE
Packt Admin
3 hrs
OR
Included in GO1 PremiumStarting from $12 per user for teamsLearn moreTry it free
OR
Included in GO1 PremiumStarting from $12 per user for teamsLearn moreTry it free

Course Overview

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!


 Target Audience

If you are a data scientist or Java developer who wants to dive into the exciting world of deep learning, then this is the right course for you. It would also be good for machine learning users working within a big data environment who want to leverage deep learning in their projects.

Learning Objectives

  • Get a practical deep dive into deep learning algorithms
  • Implement well-known 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 Convolutional Neural Network
  • Get a practical insight about how to tune models.

Business Outcomes

  • 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
Learning
Section 1: Installation and Setup
1.1 The Course Overviewvideo
1.2 Installing on Windowsvideo
1.3 Quick Startvideo
1.4 Building NN Using GPUvideo
Section 2: Neural Networks
2.1 Classification and Clusteringvideo
2.2 Softmax Functionvideo
2.3 Multilinear Regressionvideo
2.4 Logistic Regressionvideo
Section 3: Implementing Neural Nets
3.1 Gradient Descentvideo
3.2 Multilayer Perceptronvideo
3.3 Feed-Forward Neural Networksvideo
3.4 Recurrent Neural Networksvideo
Section 4: Deeper Architectures
4.1 Long Short Term Memory Unitsvideo
4.2 Convolutional Neural Networksvideo
4.3 Denoising Autoencodersvideo
4.4 Restricted Boltzmann Machinevideo
Section 5: Tuning
5.1 Hyper-Parameter Spacevideo
5.2 Fixing and Selecting Parametersvideo
5.3 Early Stoppingvideo
5.4 Testing and Evaluatingvideo