Machine Learning Algorithms And Techniques
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Machine Learning Algorithms And Techniques
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Author : Venkata Sathya Kumar Koppisetti
language : en
Publisher: RK Publication
Release Date : 2024-07-25
Machine Learning Algorithms And Techniques written by Venkata Sathya Kumar Koppisetti and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-25 with Computers categories.
Machine Learning Algorithms and Techniques an in-depth exploration of fundamental algorithms and methodologies in machine learning. Covering a range of topics, from supervised and unsupervised learning to advanced methods like ensemble learning and neural networks, the book delves into the mechanics behind key algorithms and their practical applications. With clear examples, it guides readers through model selection, evaluation, and tuning, making it ideal for students, data scientists, and practitioners aiming to strengthen their understanding of machine learning principles and effectively apply them to real-world challenges.
Machine Learning Algorithms And Techniques
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Author : Krishna Bonagiri
language : en
Publisher: RK Publication
Release Date : 2024-06-21
Machine Learning Algorithms And Techniques written by Krishna Bonagiri and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-21 with Computers categories.
Machine Learning Algorithms and Techniques the concepts, popular algorithms, and essential techniques of machine learning. A comprehensive covering supervised, unsupervised, and reinforcement learning methods while exploring key algorithms like decision trees, neural networks, clustering, and more. Practical applications and examples bring each algorithm to life, helping readers understand how these models are used to solve real-world problems. Designed for both beginners and experienced practitioners, this book is an ideal guide for mastering the fundamentals and applications of machine learning.
Mastering Machine Learning Algorithms
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Author : Giuseppe Bonaccorso
language : en
Publisher:
Release Date : 2020
Mastering Machine Learning Algorithms written by Giuseppe Bonaccorso and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computer algorithms categories.
Python Machine Learning By Example
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Author : Yuxi (Hayden) Liu
language : en
Publisher:
Release Date : 2019-02-28
Python Machine Learning By Example written by Yuxi (Hayden) Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Computers categories.
Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features Exploit the power of Python to explore the world of data mining and data analytics Discover machine learning algorithms to solve complex challenges faced by data scientists today Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you're interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You'll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you'll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you'll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn Understand the important concepts in machine learning and data science Use Python to explore the world of data mining and analytics Scale up model training using varied data complexities with Apache Spark Delve deep into text and NLP using Python libraries such NLTK and gensim Select and build an ML model and evaluate and optimize its performance Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you're a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.
Machine Learning A Comprehensive Overview Of Algorithms And Techniques
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Author :
language : en
Publisher: Xoffencerpublication
Release Date : 2023-07-04
Machine Learning A Comprehensive Overview Of Algorithms And Techniques written by and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Computers categories.
The field of artificial intelligence (AI) and computer science known as machine learning is focused on the use of data and algorithms to simulate the method in which people learn, with the goal of continuously improving the accuracy of the simulation. Machine learning has a long and illustrious history at IBM. As a result of Arthur Samuel's study (PDF, 481 KB) (link lives outside of IBM) revolving around the game of checkers, the phrase "machine learning" is often regarded as having been first used by a member of IBM's staff. Robert Nealey, who fancied himself the world's best player at checkers, challenged an IBM 7094 computer to a match in 1962 and was defeated by the machine. This accomplishment may appear little when weighed against what is now possible, yet it is recognized as a significant turning point in the development of artificial intelligence. In the past few of decades, technical advancements in storage and processing capacity have made it possible for a number of novel products based on machine learning to become available. Some examples of these products are the recommendation engine used by Netflix and autonomous vehicles. The rapidly developing discipline of data science has an essential subfield known as machine learning. Data mining initiatives involve the training of algorithms to create classifications or predictions, as well as the discovery of critical insights, through the utilization of statistical methodologies. The subsequent decisions made inside applications and enterprises are influenced by these insights, which should ideally have an effect on key growth indicators. It is expected that there will be a greater need for data scientists in the industry as big data continues to develop and flourish. They will be expected to assist in determining the business questions that are the most pertinent, as well as the data necessary to answer those questions. Frameworks that speed up the construction of solutions are usually used while developing machine learning algorithms. Some examples of such frameworks are TensorFlow and PyTorch
Machine Learning
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Author : T V Geetha
language : en
Publisher: CRC Press
Release Date : 2023-05-17
Machine Learning written by T V Geetha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-17 with Business & Economics categories.
Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms – When to use them & Why – for Application developers and Researchers Machine Learning from an Application Perspective – General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.
Mastering Machine Learning Algorithms Second Edition
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Author : Giuseppe Bonaccorso
language : en
Publisher:
Release Date : 2020-01-31
Mastering Machine Learning Algorithms Second Edition written by Giuseppe Bonaccorso and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.
Text Mining With Machine Learning
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Author : Jan Žižka
language : en
Publisher: CRC Press
Release Date : 2019-10-31
Text Mining With Machine Learning written by Jan Žižka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.
This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.
Machine Learning Algorithms And Applications
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Author : Mettu Srinivas
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-10
Machine Learning Algorithms And Applications written by Mettu Srinivas and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-10 with Computers categories.
Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniques, with each chapter dealing with a novel approach of machine learning architecture for a specific application, and then compares the results with previous algorithms. The book discusses many methods based in different fields, including statistics, pattern recognition, neural networks, artificial intelligence, sentiment analysis, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. All learning algorithms are explained so that the user can easily move from the equations in the book to a computer program.
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques
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Author : Olivas, Emilio Soria
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques written by Olivas, Emilio Soria and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.