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Master Autoencoders In Keras




KerasIT Institute


Working Professionals and Freshers


Regular Offline and Online Live Training


Week Days and Week Ends

Duration :

2 Months

Keras What will you learn?

•How To resolve errors in Keras .
•You will learn how to install Keras .
•Learn how to develop, build and deploy Keras
•Learn how to structure a large-scale project using Keras .
•Learn Keras from Scratch with Demos and Practical examples.
•Learn Keras at a minimal cost and enjoy the instructor support.
•Beginner to Advance Level: Learn to Plan, Design and Implement Keras Go through all the steps to designing a game from start to finish.Keras -Learn how to use one component inside an other i.e complex components.

Master Autoencoders in Keras Course Features

•Career guidance providing by It Expert
•Get Training from Certified Professionals
•Learn Core concepts from Leading Instructors
•Create hands-on projects at the end of the course
•We hire Top Technical Trainers for Quality Sessions
•Hands On Experience – will be provided during the course to practice
•We also provide Normal Track, Fast Track and Weekend Batches also for Working Professionals
• Our dedicated HR department will help you search jobs as per your module & skill set, thus, drastically reducing the job search time

Who are eligible for Keras

•.Net Developer, SilverLight, MVC3, Entity Framework 4, WCF, SQL/PLSQL, c#, SQL Server 2008, HTML5, .Net
•Iot, Embedded Systems, Bluetooth Low Energy, Bluetooth, Web Designing, Responsive Web Design, Visual Web Developer, Aws, Cloud Computing, Algorithm
•Java tech lead,Java Programming, Java / J2Ee Spring, Java Server Pages, Android, IOS Developer, hibernate, Spring, Core Java
•QT Developer, STB Domain, CAS, UX DESIGNER, UI Developer, HTML5, CSS3, JAVAScript, JQUERY, FIREWORKS, Adobe Photoshop, Illustratot, Embedded C++
•Software Engineer, Business Operational Analyst, Project Manager, Software Test Engineer, Android Developers, HTML5 Developers, IT Help Desk, IT Freshers


Autoencoders are a very popular neural network architecture in Deep Learning. It consists of 2 parts – Encoder and Decoder. Encoder encodes the data into some smaller dimension, and Decoder tries to reconstruct the input from the encoded lower dimension. The lowest dimension is known as Bottleneck layer. So, it can be used for Data compression. In this course we explore the different types of Autoencoders, starting from simple to complex models. We’ll also look at how to implement different Autoencoder models using Keras, which one of the most popular Deep Learning frameworks.

Eligiblity for Certification :

Machine learning Engineers, Data Scientists, Research Engineers, Software Developers