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Deep Learning Fundamentals with Keras

IBM via edX

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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.

Syllabus

Module 1 - Introduction to Deep Learning         
     - Introduction to Deep Learning
     - Biological Neural Networks
     - Artificial Neural Networks - Forward Propagation
 
Module 2 - Artificial Neural Networks
     - Gradient Descent
     - Backpropagation
     - Vanishing Gradient
     - Activation Functions

Module 3 - Deep Learning Libraries
     - Introduction to Deep Learning Libraries
     - Regression Models with Keras
     - Classification Models with Keras

Module 4 - Deep Learning Models
     - Shallow and Deep Neural Networks
     - Convolutional Neural Networks
     - Recurrent Neural Networks
     - Autoencoders

Taught by

Alex Aklson

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