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Anthony So - The Data Science Workshop: A New, Interactive Approach to Learning Data Science

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Cut through the noise and get real results with a step-by-step approach to data science

Key Features
  • Ideal for the data science beginner who is getting started for the first time
  • A data science tutorial with step-by-step exercises and activities that help build key skills
  • Structured to let you progress at your own pace, on your own terms
  • Use your physical print copy to redeem free access to the online interactive edition
Book Description

You already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. Youll learn from real examples that lead to real results.

Throughout The Data Science Workshop, youll take an engaging step-by-step approach to understanding data science. You wont have to sit through any unnecessary theory. If youre short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. Its your choice. Learning on your terms, youll build up and reinforce key skills in a way that feels rewarding.

Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, youll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. Youll even earn a secure credential that you can share and verify online upon completion. Its a premium learning experience thats included with your printed copy. To redeem, follow the instructions located at the start of your data science book.

Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. Youll learn about machine learning algorithms like a data scientist, learning along the way. This process means that youll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.

What you will learn
  • Find out the key differences between supervised and unsupervised learning
  • Manipulate and analyze data using scikit-learn and pandas libraries
  • Learn about different algorithms such as regression, classification, and clustering
  • Discover advanced techniques to improve model ensembling and accuracy
  • Speed up the process of creating new features with automated feature tool
  • Simplify machine learning using open source Python packages
Who this book is for

Our goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.

Table of Contents
  1. Introduction to Data Science in Python
  2. Regression
  3. Binary Classification
  4. Multiclass Classification with RandomForest
  5. Performing Your First Cluster Analysis
  6. How to Assess Performance
  7. The Generalization of Machine Learning Models
  8. Hyperparameter Tuning
  9. Interpreting a Machine Learning Model
  10. Analyzing a Dataset
  11. Data Preparation
  12. Feature Engineering
  13. Imbalanced Datasets
  14. Dimensionality Reduction
  15. Ensemble Learning
  16. Machine Learning Pipelines
  17. Automated Feature Engineering

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The Data Science Workshop

A New, Interactive Approach to Learning Data Science

Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, and Dr. Samuel Asare

The Data Science Workshop

Copyright 2020 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Authors: Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, and Dr. Samuel Asare

Technical Reviewers: Tianxiang Liu, Tiffany Ford, and Pritesh Tiwari

Managing Editors: Adrian Cardoza and Snehal Tambe

Acquisitions Editor: Sarah Lawton

Production Editor: Salma Patel

Editorial Board: Shubhopriya Banerjee, Bharat Botle, Ewan Buckingham, Megan Carlisle, Mahesh Dhyani, Manasa Kumar, Alex Mazonowicz, Bridget Neale, Dominic Pereira, Shiny Poojary, Abhishek Rane, Brendan Rodrigues, Erol Staveley, Ankita Thakur, Nitesh Thakur, and Jonathan Wray

First Published: January 2020

Production Reference: 1280120

ISBN: 978-1-83898-126-6

Published by Packt Publishing Ltd.

Livery Place, 35 Livery Street

Birmingham B3 2PB, UK

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