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Pro Machine Learning Algorithms

book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you;

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Machine Learning Foundations

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning;

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Ensemble Machine Learning Cookbook

Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular;

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Machine Learning with scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;

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Machine Learning with SAP

Work smarter with machine learning! Begin with core machine learning concepts-types of learning, algorithms, data preparation, and more;

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Thoughtful Machine Learning

Learn how to apply test-driven development (TDD) to machine-learning algorithms - and catch mistakes that could sink your analysis. In this;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Machine Learning Fundamentals

With the flexibility and features of scikit-learn and Python, build machine learning algorithms that optimize the programming process and;

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Machine Learning and Big Data

learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent;

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First-order and Stochastic Optimization Methods for Machine Learning

learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the;

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First-order and Stochastic Optimization Methods for Machine Learning

learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the;

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Quantum Machine Learning

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine;

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Algorithms in Machine Learning Paradigms

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse;

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Algorithms in Machine Learning Paradigms

This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse;

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Machine Learning Theoretical Foundations and Practical Applications

in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network;

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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Python Machine Learning

Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs;

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Mastering Machine Learning Algorithms

Explore and master the most important algorithms for solving complex machine learning problems. Key Features Discover high-performing;

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Machine Learning Algorithms

Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This;

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Machine Learning Using R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition;

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Distributed Machine Learning and Gradient Optimization

This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the;

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Condition Monitoring with Vibration Signals

presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance.A;

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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

machine learning problems Key Features Delve into machine learning with this comprehensive guide to scikit-learn and scientific Python Master the;

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Machine Learning in Healthcare

Machine Learning in Healthcare discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. It;

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