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IBM

Introduction to Deep Learning & Neural Networks with Keras

IBM via Coursera

Overview

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Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library. After completing this course, learners will be able to: • Describe what a neural network is, what a deep learning model is, and the difference between them. • Demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines. • Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks. • Build deep learning models and networks using the Keras library.

Syllabus

  • Introduction to Deep Learning and Neural Networks
    • In this module, you will learn about exciting applications of deep learning and why now is the perfect time to learn deep learning. You will learn about neural networks and how most deep learning algorithms are inspired by how our brain functions and the neurons process data. You will also learn about how neural networks feed data forward through the network.
  • Keras and Deep Learning Libraries
    • In this module, you will learn about the different deep learning libraries: Keras, PyTorch, and TensorFlow. You will also learn how to build regression and classification models using the Keras library.
  • Deep Learning Models
    • In this module, you will learn the difference between shallow and deep neural networks. You will also learn about convolutional networks and how to build them using the Keras library. Finally, you will also learn about recurrent neural networks and autoencoders.
  • Final Project and Course Wrap-Up
    • In this module, you will conclude the course by working on a final assignment where, you will classify aircraft damage using a pre-trained VGG16 model and generate captions using a Transformer-based pretrained model.

Taught by

Alex Aklson

Reviews

4.7 rating at Coursera based on 1721 ratings

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