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Using R for Data Analysis in Social Sciences
Using R for Data Analysis in Social Sciences
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate...
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...
Python: Data Analytics and Visualization
Python: Data Analytics and Visualization

Understand, evaluate, and visualize data About This Book - Learn basic steps of data analysis and how to use Python and its packages - A step-by-step guide to predictive modeling including tips, tricks, and best practices - Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for...

Learning scikit-learn: Machine Learning in Python
Learning scikit-learn: Machine Learning in Python

Incorporating machine learning in your applications is becoming essential. As a programmer this book is the ideal introduction to scikit-learn for your Python environment, taking your skills to a whole new level.

Overview

  • Use Python and scikit-learn to create intelligent applications
  • Apply...
Clojure for Machine Learning
Clojure for Machine Learning

In this compelling introduction to machine learning techniques and algorithms, you’ll learn how to use your knowledge of Clojure. From building systems to using machine learning techniques in cloud architecture, it’s the complete guide.

Overview

  • Covers a lot of machine learning techniques with...
Scala for Machine Learning
Scala for Machine Learning

Leverage Scala and Machine Learning to construct and study systems that can learn from data

About This Book

  • Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and source code
  • Leverage your expertise in Scala...
Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and...
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...
Machine Learning in Java: Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition
Machine Learning in Java: Helpful techniques to design, build, and deploy powerful machine learning applications in Java, 2nd Edition

Leverage the power of Java and its associated machine learning libraries to build powerful predictive models

Key Features

  • Solve predictive modeling problems using the most popular machine learning Java libraries
  • Explore data processing, machine learning, and NLP concepts...
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition
This book presents this new discipline in a very accessible form: both as a text to train the next generation of practitioners and researchers, and to inform lifelong learners like myself. Witten and Frank have a passion for simple and elegant solutions. They approach each topic with this mindset, grounding all concepts in concrete examples,...
Introduction to Data Mining and its Applications (Studies in Computational Intelligence)
Introduction to Data Mining and its Applications (Studies in Computational Intelligence)
An enormous proliferation of databases in almost every area of human endeavor has created a great demand for new, powerful tools for turning data into useful, task-oriented knowledge. In the efforts to satisfy this need, researchers have been exploring ideas and methods developed in machine learning, pattern recognition, statistical data analysis,...
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances

Create AI applications in Python and lay the foundations for your career in data science

Key Features

  • Practical examples that explain key machine learning algorithms
  • Explore neural networks in detail with interesting examples
  • Master core AI concepts with...
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