Deep Learning Fundamentals with Keras
list 5 sequences
assignment Level : Intermediate
chat_bubble_outline Language : English
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Key information

credit_card Free access
verified_user Fee-based Certificate
timer 10 hours in total

About the content

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.
  • 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.

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Prerequisite

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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
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Instructors

Alex Aklson
Ph.D., Data Scientist
IBM

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IBM

International Business Machines Corporation (commonly referred to as IBM) is an American multinational technology and consulting corporation, with headquarters in Armonk, New York. IBM manufactures and markets computer hardware, middleware and software, and offers infrastructure, hosting and consulting services in areas ranging from mainframe computers to nanotechnology.

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Platform

Edx

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