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Understanding the Role of Business Analytics
Understanding the Role of Business Analytics

This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in...

Advanced Statistics Demystified
Advanced Statistics Demystified

TAKE THE "MEAN" OUT OF ADVANCED STATISTICS

Now anyone who has mastered basic statistics can easily take the next step up. In Advanced Statistics Demystified, experienced statistics instructor Larry J. Stephens provides an effective, anxiety-soothing, and totally painless way to learn advanced statistics --...

Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Build, scale, and deploy deep neural network models using the star libraries in Python

Key Features

  • Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras
  • Build, deploy, and scale end-to-end deep neural network models in a production...
Robust Statistics: Theory and Methods (Probability and Statistics)
Robust Statistics: Theory and Methods (Probability and Statistics)
Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and...
Bayesian Biostatistics and Diagnostic Medicine
Bayesian Biostatistics and Diagnostic Medicine
Bayesian methods are being used more often than ever before in biology and medicine. For example, at the University of Texas MD Anderson Cancer Center, Bayesian sequential stopping rules routinely are used for the design of clinical trials. This book is based on the author’s experience working with a variety of...
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques

Build next-generation artificial intelligence systems with Java

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using...
A Statistical Approach to Neural Networks for Pattern Recognition (Wiley Series in Computational Statistics)
A Statistical Approach to Neural Networks for Pattern Recognition (Wiley Series in Computational Statistics)
"The book provides an excellent introduction to neutral networks from a statistical perspective." (International Statistical Review, 2008)

"Successful connects logistic regression and linear discriminant analysis, thus making it critical reference and self-study guide for students and professionals alike in the...

Linear Regression Analysis: Theory and Computing
Linear Regression Analysis: Theory and Computing

This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is...

TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

Learn how to solve challenging machine learning problems with TensorFlow, Google’s revolutionary new software library for deep learning. If you have some background in basic linear algebra and calculus, this practical book introduces machine-learning fundamentals by showing you how to design systems capable of detecting objects...

Learning Bayesian Models with R
Learning Bayesian Models with R

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

About This Book

  • Understand the principles of Bayesian Inference with less mathematical equations
  • Learn state-of-the art Machine Learning methods
  • Familiarize...
Practical Data Science with R
Practical Data Science with R

Summary

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language...

Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
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