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Applied Reinforcement Learning with Python

Who This Book Is For Data scientists, machine learning engineers and software engineers familiar with machine learning and deep;

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Data-Driven Science and Engineering

intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics;

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Applied Analytics through Case Studies Using SAS and R

understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data;

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Python Machine Learning Case Studies

of Python from a machine learning point of view Who This Book Is For Data scientists, data analysts, artificial intelligence engineers, big data;

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Practical Time Series Analysis Prediction with Statistics and Machine Learning

digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time;

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Data Science

for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software;

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Data Science

for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software;

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Statistics and Probability with Applications for Engineers and Scientists Using MINITAB, R and JMP

MINITAB, R and JMP is an excellent text for graduate level data science students, and engineers and scientists. It is also an ideal introduction;

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Hands-on Machine Learning with Python

sequences in recurrent neural networks and long short term memory Who This Book Is For Data scientists, machine learning engineers, and;

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Human-in-the-Loop Machine Learning

* Real-world use cases from well-known data scientists For software developers and data scientists with some basic Machine Learning;

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Machine Learning and Artificial Intelligence in Marketing and Sales

methods for addressing marketing and sales problems will benefit most if they are exposed to how AI and machine learning have been applied;

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Agile Machine Learning

Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists;

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Machine Learning for Engineers

All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive;

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Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization;

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Deep Learning from Scratch Building with Python from First Principles

software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience;

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Empirical Modeling and Data Analysis for Engineers and Applied Scientists

learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar;

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Advances in Machine Learning Applications in Software Engineering

provides analysis, characterization, and refinement of software engineering data in terms of machine learning methods. This book depicts;

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Machine Learning Engineering with Python

Discover how to build your own wrapper libraries for encapsulating your data science and machine learning logic and solutions Understand what;

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Beginning Apache Spark 3

efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing;

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97 Things Every Data Engineer Should Know

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful;

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Artificial Intelligence in Medical Sciences and Psychology

more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers;

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Human-Machine Shared Contexts

. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning;

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Representation Learning

selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning;

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Representation Learning

selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning;

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Machine Learning and Artificial Intelligence for Agricultural Economics

This book discusses machine learning and artificial intelligence (AI) for agricultural economics. It is written with a view towards;

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Critical Approaches to Information Retrieval Research

of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists;

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Machine Learning

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area;

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