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Search - Hands On Machine Learning with Python

Hands On Machine Learning with Python
Author: John Anderson

***** BUY NOW (will soon return to 25.89 $) ***** MONEY BACK GUARANTEE BY AMAZON (See Below FAQ) ***** >****** Free eBook for customers who purchase the print book from Amazon ****** Are you thinking of learning more about Machine Learning using Python? (For beginners) This book is for you. It would seek to explain common terms and algorithms... more » in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using machine learning. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses. To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning.Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird?s eye view of current techniques and approaches. What?s Inside This Book? < Overview of Python Programming LanguageStatisticsProbabilityThe Data Science ProcessMachine LearningSupervised Learning AlgorithmsUnsupervised Learning AlgorithmsSemi-supervised Learning AlgorithmsReinforcement Learning AlgorithmsOverfitting and UnderfittingPython Data Science ToolsJupyter NotebookNumerical Python (Numpy)PandasScientific Python (Scipy)MatplotlibScikit-LearnK-Nearest NeighborsNaive BayesSimple and Multiple Linear RegressionLogistic RegressionGeneralized Linear ModelsDecision Trees and Random ForestNeural NetworksPerceptronsBackpropagationClusteringK-means with Scikit-LearnBottom-up Hierarchical ClusteringK-means ClusteringNetwork AnalysisBetweenness centralityEigenvector CentralityRecommender SystemsMulti-Class ClassificationPopular Classification AlgorithmsSupport Vector MachineDeep Learning using TensorFlowDeep Learning Case Studies Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to smash Machine Learning from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you?ll be OK. Q: Does this book include everything I need to become a Machine Learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at contact@aisciences.net.

ISBN-13: 9781724731968
ISBN-10: 1724731963
Publication Date: 8/6/2018
Pages: 223
Edition: 1
Rating:

0 stars, based on 0 rating

Publisher: CreateSpace Independent Publishing Platform
Book Type: Paperback
Members Wishing: 0
Reviews: Amazon | Write a Review

Genres:

Computers & Technology >> Computer Science >> AI & Machine Learning >> Computer Vision & Pattern Recognition

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