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Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so...
Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud
Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book?Amazon, Microsoft, Google, and PythonAnywhere.

You will work through a series of common Python data science problems...

TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0
TensorFlow 2.0 Quick Start Guide: Get up to speed with the newly introduced features of TensorFlow 2.0

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.

Key Features

  • Train your own models for effective prediction, using high-level Keras API
  • Perform supervised and unsupervised machine learning and learn...
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale
Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale

Build effective regression models in R to extract valuable insights from real data

Key Features

  • Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values
  • From Simple Linear Regression...
Mastering Machine Learning With scikit-learn
Mastering Machine Learning With scikit-learn

Apply effective learning algorithms to real-world problems using scikit-learn

About This Book

  • Design and troubleshoot machine learning systems for common tasks including regression, classification, and clustering
  • Acquaint yourself with popular machine learning algorithms, including...
College Algebra in Context (4th Edition)
College Algebra in Context (4th Edition)
College Algebra in Context is designed for a course in algebra that is based on data analysis, modeling, and real-life applications from the management, life, and social sciences. The...
Data Analysis Using SAS Enterprise Guide
Data Analysis Using SAS Enterprise Guide

The present book, Data Analysis Using SAS Enterprise Guide, provides readers with an overview of Enterprise Guide, the newest point-and-click interface from SAS. SAS Enterprise Guide is a graphical user (point-and-click) interface to the main SAS application, having relatively recently replaced the Analyst interface, which itself had replaced...

Mastering Machine Learning with R
Mastering Machine Learning with R

Master machine learning techniques with R to deliver insights for complex projects

About This Book

  • Get to grips with the application of Machine Learning methods using an extensive set of R packages
  • Understand the benefits and potential pitfalls of using machine learning methods
  • ...
Introduction to Real Analysis: An Educational Approach
Introduction to Real Analysis: An Educational Approach

An accessible introduction to real analysis and its connection to elementary calculus

Bridging the gap between the development and history of real analysis, Introduction to Real Analysis: An Educational Approach presents a comprehensive introduction to real analysis while also offering a survey of the field. With its...

Mastering .NET Machine Learning
Mastering .NET Machine Learning

About This Book

  • Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0
  • Set up your business application to start using machine learning techniques
  • Familiarize the user with some of the more common .NET libraries for machine learning
  • Implement...
Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Assessing and Improving Prediction and Classification: Theory and Algorithms in C++
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting.  This book presents many important techniques for building...
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