Machine Learning with scikit learn Quick Start Guide Book [PDF] Download

Download the fantastic book titled Machine Learning with scikit learn Quick Start Guide written by Kevin Jolly, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Machine Learning with scikit learn Quick Start Guide", which was released on 30 October 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.

Summary of Machine Learning with scikit learn Quick Start Guide by Kevin Jolly PDF

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Key FeaturesBuild your first machine learning model using scikit-learnTrain supervised and unsupervised models using popular techniques such as classification, regression and clusteringUnderstand how scikit-learn can be applied to different types of machine learning problemsBook Description Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides. This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models. Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions. What you will learnLearn how to work with all scikit-learn's machine learning algorithmsInstall and set up scikit-learn to build your first machine learning modelEmploy Unsupervised Machine Learning Algorithms to cluster unlabelled data into groupsPerform classification and regression machine learningUse an effective pipeline to build a machine learning project from scratchWho this book is for This book is for aspiring machine learning developers who want to get started with scikit-learn. Intermediate knowledge of Python programming and some fundamental knowledge of linear algebra and probability will help.


Detail About Machine Learning with scikit learn Quick Start Guide PDF

  • Author : Kevin Jolly
  • Publisher : Packt Publishing Ltd
  • Genre : Mathematics
  • Total Pages : 164 pages
  • ISBN : 1789347378
  • PDF File Size : 41,9 Mb
  • Language : English
  • Rating : 5/5 from 1 reviews

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Machine Learning with scikit-learn Quick Start Guide

Machine Learning with scikit-learn Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 42,5 Mb
  • Release Date : 30 October 2018
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Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Key FeaturesBuild your first machine learning model using scikit-learnTrain supervised and unsupervised models using popular

fastText Quick Start Guide

fastText Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 25,5 Mb
  • Release Date : 26 July 2018
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Perform efficient fast text representation and classification with Facebook's fastText library Key Features Introduction to Facebook's fastText library for NLP Perform efficient word representations, sentence classification, vector representation Build better,

Machine Learning with Apache Spark Quick Start Guide

Machine Learning with Apache Spark Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 40,5 Mb
  • Release Date : 26 December 2018
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Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time

Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 43,7 Mb
  • Release Date : 25 April 2019
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Explore the different data mining techniques using the libraries and packages offered by Python Key FeaturesGrasp the basics of data loading, cleaning, analysis, and visualizationUse the popular Python libraries such

Natural Language Processing with Python Quick Start Guide

Natural Language Processing with Python Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 31,7 Mb
  • Release Date : 30 November 2018
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Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key FeaturesA no-math, code-driven programmer’s guide

Machine Learning Applications in Industrial Solid Ash

Machine Learning Applications in Industrial Solid Ash
  • Publisher : Elsevier
  • File Size : 24,5 Mb
  • Release Date : 01 December 2023
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Offering the ability to process large or complex datasets, machine learning (ML) holds huge potential to reshape the whole status for solid ash management and recycling. Machine Learning for Solid

Geospatial Data Science Quick Start Guide

Geospatial Data Science Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 43,8 Mb
  • Release Date : 31 May 2019
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Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used

Machine Learning with Scala Quick Start Guide

Machine Learning with Scala Quick Start Guide
  • Publisher : Packt Publishing Ltd
  • File Size : 35,5 Mb
  • Release Date : 30 April 2019
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Supervised and unsupervised machine learning made easy in Scala with this quick-start guide. Key FeaturesConstruct and deploy machine learning systems that learn from your data and give accurate predictionsUnleash the

Data Science Concepts and Techniques with Applications

Data Science Concepts and Techniques with Applications
  • Publisher : Springer Nature
  • File Size : 55,6 Mb
  • Release Date : 02 April 2023
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This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other