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...
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...
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...
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...
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...
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...
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...
