Hands-On Keras for Machine Learning Engineers | Packt Publishing
Learn to design and build deep learning models with Keras
Machine Learning,Development,Data Science
Lectures -68
Duration -2 hours
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Course Description
Welcome to hands-on Kera's for machine learning engineers. This is a carefully structured course to guide you in your journey to learn deep learning in Python with Kera's. Discover the Kera's Python library for deep learning and learn the process of developing and evaluating deep learning models using it.
There are two top numerical platforms for developing deep learning models; they are Theano, developed by the University of Montreal, and Tensor Flow developed at Google. Both were developed for use in Python and both can be leveraged by the super-simple-to-use Kera's library. Kera's wraps the numerical computing complexity of Theano and Tensor Flow, providing a concise API that we will use to develop our own neural network and deep learning models. Kera's has become the gold standard in the applied space for rapid prototyping deep learning models.
This course is a hands-on guide. It is a playbook and a workbook intended for you to learn by doing and then apply your new understanding to your own deep learning Kera's models.
All resources and code files for this course are placed here: https://github.com/PacktPublishing/Hands-On-Keras-for-Machine-Learning-Engineers
Audiences:
This course is for developers, machine learning engineers, and data scientists that want to learn how to get the most out of Kera's. You do not need to be a machine learning expert, but it would be helpful if you knew how to navigate a small machine learning problem using Sickest-Learn.
Goals
- Develop and evaluate neural network models end-to-end
- Build larger models for image and text data
- Understand the anatomy of a Keras model
- Evaluate the performance of a deep learning Keras model
- Build end-to-end regression and classification models in Keras
- Learn how to use checkpointing to save the best model run
Prerequisites
- Basic concepts such as cross-validation and one-hot encoding used in lessons and projects are described, but only briefly. With all of this in mind, this is an entry-level course on the Keras library.
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Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
4 Lectures
-
Introduction 01:35 01:35
-
What You'll Learn in this Course 01:33 01:33
-
Is this Course Right for You? 00:51 00:51
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What is Keras? 01:24 01:24
Foundations
23 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Going Deeper with Keras
15 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Convolutional Neural Networks
17 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Recurrent Neural Networks
9 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
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Packt Publishing
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