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Hands-on Scikit-learn for Machine Learning
Hands-on Scikit-learn for Machine Learning

Hands-on Scikit-learn for Machine Learning: Tackle real-world Machine Learning problems using Scikit-learn to quickly build a portfolio of practical Machine Learning tools

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Profile Icon Farhan Nazar Zaidi
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€18.99 per month
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Aug 2018 9hrs 3mins 1st Edition
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€111.99
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Renews at €18.99p/m
Arrow left icon
Profile Icon Farhan Nazar Zaidi
Arrow right icon
€18.99 per month
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Aug 2018 9hrs 3mins 1st Edition
Video
€111.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€111.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Apply the Machine Learning techniques and processes and widely used functions Scikit-learn has to offer for a particular task.
  • With practical hands-on approach, build strong intelligent ML systems with minimal effort
  • Explore datasets from a diverse set of ML problem domains, applying different models and techniques.

Description

Scikit-learn is arguably the most popular Python library for Machine Learning today. Thousands of Data Scientists and Machine Learning practitioners use it for day to day tasks throughout a Machine Learning project’s life cycle. Due to its popularity and coverage of a wide variety of ML models and built-in utilities, jobs for Scikit-learn are in high demand, both in industry and academia. If you’re an aspiring machine learning engineer ready to take real-world projects head-on, Hands-on Scikit-Learn for Machine Learning will walk you through the most commonly used models, libraries, and utilities offered by Scikit-learn. By the end of the course, you will have a set of ML problem-solving tools in the form of code modules and utility functions based on Scikit-learn in one place, instead of spread over several books and courses, which you can easily use on real-world projects and data sets. All the code and supporting files for this course are available on Github at: https://github.com/PacktPublishing/Hands-on-Scikit-learn-for-Machine-Learning-V-

Who is this book for?

If you are a software developer, machine learning engineer, or data analyst and want to use Scikit-learn for different Machine Learning and analytics tasks, this course is for you. You need to have a very basic understanding of Machine Learning and Data Analytics. However, no knowledge of Scikit-learn is needed. Python programming knowledge and a basic understanding of Numpy and the Pandas library are assumed.

What you will learn

  • Tackle real-world problems in Machine Learning through a structured process using Scikit-learn
  • Achieve substantially more in less time and with much less code by leveraging the power and simplicity of Scikit-learn
  • Develop a thorough understanding of core predictive analytics with regression, classification, and unsupervised learning such as clustering and PCA
  • Create ensemble models with Random-Forest and Gradient-boosting methods and see your model performance improve drastically
  • Build a portfolio of tools and techniques that can readily be applied to your own projects
  • Discover the intuition behind contemporary Machine Learning models and algorithms without going into deep mathematical details
  • Develop the ability to evaluate and improve the accuracy and performance of Machine Learning models
  • Explore the foundations of text analytics and develop a set of tools to apply to your common text-analysis tasks

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 28, 2018
Length: 9hrs 3mins
Edition : 1st
Language : English
ISBN-13 : 9781789137132
Category :
Languages :

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Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
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Product Details

Publication date : Aug 28, 2018
Length: 9hrs 3mins
Edition : 1st
Language : English
ISBN-13 : 9781789137132
Category :
Languages :

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Table of Contents

8 Chapters
Getting Started with a Simple ML Model in Scikit-learn Chevron down icon Chevron up icon
Classification Models Chevron down icon Chevron up icon
Supervised Machine Learning – Regression Chevron down icon Chevron up icon
Unsupervised Learning —Dimensionality Reduction Chevron down icon Chevron up icon
Unsupervised Learning – Clustering Chevron down icon Chevron up icon
Improving ML Model Performance Chevron down icon Chevron up icon
Creating Pipelines and Advanced Model Selection Chevron down icon Chevron up icon
Handling Text Data with Scikit-learn Chevron down icon Chevron up icon

Customer reviews

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Hari Oct 24, 2023
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One of the best course
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