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Data Science Algorithms in a Week

to gain new knowledge from existing data as well. Data Science Algorithms in a Week addresses all problems related to accurate and efficient;

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Data Science Algorithms in a Week

algorithms * Learn to use machine learning algorithms in a period of just 7 days Who This Book Is For This book is for aspiring data science;

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Data Mining Concept Animation Library

algorithms, we need a better perspective on a collection of data mining algorithms rather than just their formal definitions. In this research work;

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Data Science Fundamentals for Python and MongoDB

with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the;

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Data Science

in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel;

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Principles of Data Mining

. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately;

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Data Structures and Algorithms in Computer Science

Data structure refers to the assimilation of data in a way so that it can be used efficiently. The important types of data structures are;

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On the Epistemology of Data Science

This book addresses controversies concerning the epistemological foundations of data science: Is it a genuine science? Or is data science;

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Algorithms and Data Structures

Algorithms and data structures lie at the heart of computer science, and are essential tools for every practising programmer. This book;

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Optimization for Data Analysis

text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data;

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Responsible Data Science

delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the;

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Algorithms and Data Structures in C++

Algorithms and Data Structures in C++ introduces modern issues in the theory of algorithms, emphasizing complexity, graphs, parallel;

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Problem Solving with Algorithms and Data Structures Using Python

solving. The authors cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data;

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Data Science in Theory and Practice - Techniques for Big Data Analytics and Complex Data Sets

and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various;

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Data Mining and Knowledge Discovery With Evolutionary Algorithms

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become;

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Algorithms for Data Science

algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data;

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Algorithms for Data Science

algorithms to new problems and carry out innovative analyses. This book has three parts:(a) Data Reduction: Begins with the concepts of data;

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Hands-On Data Science with R

A hands-on guide for professionals to perform various data science tasks in R Key Features Explore the popular R packages for data science;

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Computer Science - Theory and Applications

; computational social choice; quantum computing and quantum cryptography; theoretical aspects of big data. The conference was cancelled as a live;

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Foundations of Data Science for Engineering Problem Solving

problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal;

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Foundations of Data Science for Engineering Problem Solving

problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal;

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Data Science with Java

science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the;

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Industry 4.0, AI, and Data Science

overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates;

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Bio inspired Algorithms for Data Streaming and Visualization Big Data Managemen

, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to;

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40 Algorithms Every Programmer Should Know

experience is a must, knowledge of data science will be helpful but not necessary.;

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Principles of Data Science

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces;

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Machine Learning Algorithms

* Understand the feature selection and feature engineering process * Assess performance and error trade-offs for Linear Regression * Build a data;

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