Deep Learning Using Keras - A Complete and Compact Guide for Beginners

Preview this course

In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.

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88 on-demand videos & exercises
Level: Beginner
English
9hrs 34mins
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What to know about this course

The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features from data without human intervention. That makes deep learning the base of all future self-intelligent systems. This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries—Theano and TensorFlow—and the API for dealing with these called Keras. Then, before we jump into deep learning, we will have an elaborate theory session about the basic structure of artificial neuron and neural networks, and about activation functions, loss functions, and optimizers.

Furthermore, we will create deep learning multi-layer neural network models for a text-based dataset and then convolutional neural networks for an image-based dataset. You will also learn how the basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work. Then, we will use different techniques to improve the quality of a model and perform optimization using image augmentation. By the end of this course, you will have a complete understanding of deep learning and will be able to implement these skills in your own projects. The complete code bundle for this course is available at https://github.com/PacktPublishing/Deep-Learning-using-Keras---A-Complete-and-Compact-Guide-for-Beginners

Who's this course for?

This course is designed for beginners who want to learn basic to advanced deep learning and have basic computer knowledge.

What you'll learn

  • Learn the basics of Python programming.
  • Use different Python libraries such as NumPy, Matplotlib, and Pandas.
  • Understand the basic structure of artificial neurons and neural networks.
  • Explore activation functions, loss functions, and optimizers.
  • Create deep learning multi-layer neural network models for a text-based dataset.
  • Create convolutional neural networks for an image-based dataset.

Key Features

  • The course explains how the exam is structured, the way that the questions should be approached and how to study successfully to pass.
  • The course also includes invaluable advice on the best way to prepare and what to expect from the testing process.

Course Curriculum

About the Author

Abhilash Nelson

Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than 8 years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design. Abhilash Nelson is a pioneering, talented, and security-oriented Android/iOS mobile and PHP/Python web application developer with more than eight years of IT experience involving designing, implementing, integrating, testing, and supporting impactful web and mobile applications. He has a master's degree in computer science and engineering and has PHP/Python programming experience, which is an added advantage for server-based Android and iOS client applications. Abhilash is currently a senior solution architect managing projects from start to finish to ensure high quality and innovative and functional design.