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IBM

Deep Learning Fundamentals with Keras

IBM via edX

Overview

Please Note: Learners who successfully complete this IBM course can earn a skill badge —a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

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 presentsimplified explanations to some oftoday'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 fordeep learning skills-- and the job salaries of deep learning practitioners -- arecontinuing to grow, as AI becomes more pervasive in our societies. This course will help you build the knowledge you need to future-proofyour career.

Syllabus

Module1 - Introduction to Deep Learning
- Introduction to Deep Learning
- Biological Neural Networks
- Artificial Neural Networks - Forward Propagation

Module2 -Artificial Neural Networks
- Gradient Descent
- Backpropagation
- Vanishing Gradient
- Activation Functions

Module3 - Deep Learning Libraries
- Introduction to Deep Learning Libraries
- Regression Models with Keras
- Classification Models with Keras

Module4 -Deep Learning Models
- Shallow and Deep Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Autoencoders

Taught by

Alex Aklson

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