Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Buy

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.

The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets.

Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. 

At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.

What You’ll Learn

  • Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions.
  • Design, develop, train, validate, and deploy deep neural networks using the Keras framework
  • Use best practices for debugging and validating deep learning models
  • Deploy and integrate deep learning as a service into a larger software service or product
  • Extend deep learning principles into other popular frameworks

Who This Book Is For 

Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.
(HTML tags aren't allowed.)

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field.

...
Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition
Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition

Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data

Key Features

  • Perform complex bioinformatics analysis using the most important Python libraries and applications
  • Implement next-generation sequencing,...
Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...


Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Applying Predictive Analytics: Finding Value in Data
Applying Predictive Analytics: Finding Value in Data

This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be...

Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks

Key Features

  • Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision
  • Combine the power of Python, Keras, and TensorFlow to...
©2020 LearnIT (support@pdfchm.net) - Privacy Policy