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Mastering Deep Learning Using Apache Spark

Mastering Deep Learning Using Apache Spark

In this course, you’ll learn about the major branches of AI and get familiar with several core models of Deep Learning in its natural way.

Overview

Description
Develop industrial solutions based on deep learning models with Apache Spark

Deep learning has solved tons of interesting real-world problems in recent years. Apache Spark has emerged as the most important and promising machine learning tool and currently a stronger challenger of the Hadoop ecosystem. In this course, you’ll learn about the major branches of AI and get familiar with several core models of Deep Learning in its natural way.

You’ll begin with building deep learning networks to deal with speech data and explore tricks to solve NLP problems and classify video frames using RNN and LSTMs. You’ll also learn to implement the anomaly detection model that leverages reinforcement learning techniques to improve cyber security.

Moving on, you’ll explore some more advanced topics by performing prediction classification on image data using the GAN encoder and decoder. Then you’ll configure Spark to use multiple workers and CPUs to distribute your Neural Network training. Finally, you’ll track progress, solve the most common problems in your neural network, and debug your models that run within the distributed Spark engine.

About the Author

Tomasz Lelek

Tomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He has worked with Spark API and the ML API for the past five years and has production experience in processing petabytes of data.

He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. He was a speaker at conferences in Poland, Confitura and JDD (Java Developers Day), and the Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference.

Course Information

Basics of Machine Learning

Configure a Convolutional Neural Network (CNN) to extract value from images
Create a deep network with multiple layers to perform computer vision
Classify speech and audio data
Leverage RNN and LSTMs for video classification for hospital data
Improve cybersecurity with deep reinforcement learning
Use a generative adversarial network for training
Create highly distributed algorithms using Spark

This course is for machine learning experts, AI experts, and data scientist experts who wish to learn about implementations with distributed deep learning. In summary, you’ll be a DL expert in a short time.

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Course Specifications

Our great AI and Machine Learning courses include Artificial Intelligence, Coding and Programming. 

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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