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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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Mastering Machine Learning Algorithms

machine learning problems Key Features Updated to include new algorithms and techniques Code updated to Python 3.8 & TensorFlow 2.x New coverage;

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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us

Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master;

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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 Foundations

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

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Hands-on Scikit-Learn for Machine Learning Applications

Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The;

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Mastering Machine Learning for Penetration Testing

Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security;

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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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Mastering Excel VBA and Machine Learning

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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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Python Deep Learning

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. About This Book;

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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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Mastering Machine Learning with scikit-learn -

Use scikit-learn to apply machine learning to real-world problems About This Book * Master popular machine learning models including;

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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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