Deep Learning Fundamentals with Keras

Provided by IBM
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Intermediate
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New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using the popular Keras library.

Part of 1 program:
Course Format:Instructor-Led
Start Date:Mar 20, 2019

What you will learn

  • You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
  • You will learn about neural networks and how they learn and update their weights and biases.
  • You will learn about the vanishing gradient problem.
  • You will learn about building a regression model using the Keras library.
  • You will learn about building a classification model using the Keras library.
  • You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the Keras library.
  • You will learn about unsupervised learning models such as autoencoders.

Overview

Looking to kickstart a career in deep learning? Look no further. This course will introduce you to the field of deep learning and teach you the fundamentals. You will learn about some of the exciting applications of deep learning, the basics fo neural networks, different deep learning models, and how to build your first deep learning model using the easy yet powerful library Keras. 

This course will present simplified explanations to some of today's hottest topics in data science, including: 
  • What is deep learning?
  • How do neural networks learn and what are activation functions?
  • What are deep learning libraries and how do they compare to one another?
  • What are supervised and unsupervised deep learning models?
  • How to use Keras to build, train, and test deep learning models?
The demand for deep learning skills-- and the job salaries of deep learning practitioners -- are continuing to grow, as AI becomes more pervasive in our societies. This course will help you build the knowledge you need to future-proof your career.

Before you start

  • Instructor-Led: course contains assignments and exams that have specific due dates, and you complete the course within a defined time period.
  • Course ends: Mar 20, 2019

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