Deep Learning with Keras and TensorFlow

COURSE INTRODUCTION

Deep Learning is one of the most exciting and promising segments of Artificial Intelligence and machine learning technologies. This deep learning course with TensorFlow is designed to help you master deep learning techniques and build deep learning models using TensorFlow, the open-source software library developed by Google for the purpose of conducting machine learning and deep neural networks research. It is one of the most popular software platforms used for deep learning and contains powerful tools to help you build and implement artificial neural networks.

Advancements in deep learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in deep learning models, learn to operate TensorFlow to manage neural networks and interpret the results.

KEY FEATURES

  • 40 hours of instructor-led training
  • Real-life industry based projects
  • 24*7 support with dedicated project mentoring sessions
  • Flexibility to choose classes
  • Dedicated mentoring session from our Industry expert faculties

COURSE OBJECTIVES

After finish the course, student will have knowledge and skills to:

  • By the end of this deep learning course with TensorFlow, you will be able to accomplish the following:
  • Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
  • Implement deep learning algorithms, understand neural networks and traverse the layers of data abstraction which will empower you to understand data like never before
  • Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks and high-level interfaces
  • Build deep learning models in TensorFlow and interpret the results
  • Understand the language and fundamental concepts of artificial neural networks
  • Troubleshoot and improve deep learning models
  • Build your own deep learning project
  • Differentiate between machine learning, deep learning and artificial intelligence

AUDIENCE

  • Software engineers
  • Data scientists
  • Data analysts
  • Statisticians with an interest in deep learning

PREREQUISITES

  • Familiarity with programming fundamentals
  • Fair understanding of basics of statistics and mathematics

EXAM & CERTIFICATION

Unlock Simplilearn certificate

  • Attend one complete batch
  • Complete and attain evaluation of any one of the given projects

Who provides the certification and how long is it valid for?

Upon successful completion of the Deep Learning online training course, you will be awarded an industry-recognized course completion certificate from Simplilearn which has a lifelong validity.

COURSE CONTENTS

Lesson 00 - Introduction to TensorFlow

Lesson 01 - Perceptrons

Lesson 02 - Activation Functions

Lesson 03 - Artificial Neural Networks

Lesson 04 - Gradient Descent and Backpropagation

Lesson 05 - Optimization and Regularization

Lesson 06 - Intro to Convolutional Neural Networks

Lesson 07 - Introduction to Recurrent Neural Networks

Lesson 08 - Deep Learning applications

CÓ THỂ BẠN QUAN TÂM
Array
(
)