Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Hands-On Predictive Analytics with Python
Hands-On Predictive Analytics with Python

Hands-On Predictive Analytics with Python: Master the complete predictive analytics process, from problem definition to model deployment

eBook
€20.98 €29.99
Paperback
€36.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
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.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

Hands-On Predictive Analytics with Python

Problem Understanding and Data Preparation

In the last chapter, we learned about the predictive analytics process; we also learned about some of the fundamental definitions and the main libraries in the Python data ecosystem. In this chapter, we will start getting our hands on a couple of datasets and delve deeper into the first and second phases of the predictive analytics process: Problem understanding and definition and Data collection and preparation.

In the first part of this chapter, we talk about some of the most important considerations when defining and understanding the problem: having enough context and domain knowledge about the problem, and defining what is being predicted and the data that we have to work with. This phase also includes proposing a solution; we talk about some of the main topics to consider.

We put this idea into practice in the second part of the...

Technical requirements

  • Python 3.6 or higher
  • Jupyter Notebook
  • Recent versions of the following Python libraries: NumPy, pandas, and matplotlib

Understanding the business problem and proposing a solution

In this section, we talk about problem understanding and definition, and other aspects related to the activity of defining the problem that will be solved using predictive analytics. Of course, the specifics of this stage depend entirely on the project, so we will provide only very generic guidance about this. However, when discussing the practical examples, we will touch on some of the important considerations when understanding the problem in a predictive analytics project.

Context is everything

What we call Problem understanding and definition is the first stage in the process, and as we mentioned in the last chapter, this is a key stage because here is where we...

Practical project – diamond prices

In this section, we introduce the diamond prices dataset. Let's start implementing the predictive analytics process we discussed in the first chapter. We begin with the stage we just discussed in the last section, Problem understanding and definition.

Diamond prices – problem understanding and definition

A new company, Intelligent Diamond Reseller (IDR), wants to get into the business of reselling diamonds. They want to innovate in the business, so they will use predictive modeling to estimate how much the market will pay for diamonds. Of course, to sell diamonds in the market, first they have to buy them from the producers; this is where predictive modeling becomes useful...

Practical project – credit card default

This is our second practical project, in which we will solve a classification problem. As we did with the diamonds dataset, let's begin the predictive analytics process for this new project by understanding and defining the problem.

Credit card default – problem understanding and definition

TFI is the Taiwanese Financial Institution and it offers credit cards. It has been detecting an increase in defaults among its customers; a default is defined as a customer missing a payment for a single month. This situation is negatively affecting the revenue of the company and they know they can do something about it if they could anticipate which credit card holders are going...

Summary

In this chapter, we have covered two stages in the predictive analytics process: Problem understanding and definition and Data collection and preparation. We learned about important considerations for understanding the problem and proposing the solution; we also introduced the concepts of regression tasks and classification tasks. We got our hands dirty with a couple of datasets that we will continue within the following chapters, and in going through the second phase, Data collection and preparation, with these datasets, we introduce important concepts such as one-hot encoding, outliers, missing values, collinearity, and feature engineering. In addition, we got to practice how to use pandas for loading, exploring, transforming, and preparing a dataset to continue with the next stages of the predictive analytics process.

In the next chapter, we will study the goals of...

Further reading

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects
  • Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations
  • Learn to deploy a predictive model's results as an interactive application

Description

Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming.

Who is this book for?

This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.

What you will learn

  • Get to grips with the main concepts and principles of predictive analytics
  • Learn about the stages involved in producing complete predictive analytics solutions
  • Understand how to define a problem, propose a solution, and prepare a dataset
  • Use visualizations to explore relationships and gain insights into the dataset
  • Learn to build regression and classification models using scikit-learn
  • Use Keras to build powerful neural network models that produce accurate predictions
  • Learn to serve a model s predictions as a web application

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 28, 2018
Length: 330 pages
Edition : 1st
Language : English
ISBN-13 : 9781789138719
Vendor :
Google
Category :
Languages :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
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.
Subscribe now
View plans & pricing

Product Details

Publication date : Dec 28, 2018
Length: 330 pages
Edition : 1st
Language : English
ISBN-13 : 9781789138719
Vendor :
Google
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
€18.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
€189.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts
€264.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just €5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 94.97
Artificial Intelligence and Machine Learning Fundamentals
€24.99
Data Analysis with Python
€32.99
Hands-On Predictive Analytics with Python
€36.99
Total 94.97 Stars icon

Table of Contents

10 Chapters
The Predictive Analytics Process Chevron down icon Chevron up icon
Problem Understanding and Data Preparation Chevron down icon Chevron up icon
Dataset Understanding – Exploratory Data Analysis Chevron down icon Chevron up icon
Predicting Numerical Values with Machine Learning Chevron down icon Chevron up icon
Predicting Categories with Machine Learning Chevron down icon Chevron up icon
Introducing Neural Nets for Predictive Analytics Chevron down icon Chevron up icon
Model Evaluation Chevron down icon Chevron up icon
Model Tuning and Improving Performance Chevron down icon Chevron up icon
Implementing a Model with Dash Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.4
(8 Ratings)
5 star 75%
4 star 12.5%
3 star 0%
2 star 0%
1 star 12.5%
Filter icon Filter
Top Reviews

Filter reviews by




reviewer of books #102395141 Dec 01, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is really educational content. My computer science graduate course used this textbook and the coding and problems in the book teach you alot. The majority of the code ran as written. I suspect there's some version conflicts between my interpreter and the book. There's a few errors/typos in the code, but they have a free downloadable jupyter notebook version that written and runs correctly but you have to go to their site. Learned alot about regression and classification problems, and this book doesn't require loads of math knowledge to get the point. If you have some python experience this book should be rather straightforward and useful.
Amazon Verified review Amazon
roudan Nov 15, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I love it. It is clear and well written.
Amazon Verified review Amazon
AGUILAR MONTOYA HUGO GEOVANNY Apr 08, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Hands-On Predictive Analytics with Python is a practical manual that will lead you from the basics of analysis to a model deployment. It starts with theroy on the predictive analytics process from the very beggining (problem definition, data collection and preparation, etc.) that more advanced readers migth skip. However, in same Chapter One, theory of Python starts, so if you are a first timer on this tool, it will be very useful.Then, the manual gets better, with EDA, Machine Learning, and Neural Nets becoming the chapters. This is a must read and practice manual for everyone who wants to learn a begginer's lever on Python applied to analytics. Have a great practice time while learning deep Python!
Amazon Verified review Amazon
Susie GJ Mar 04, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Recommended book if you want to understand how to do predictive analytics in practice, I have followed many online resources about predictive modelling, but they never go beyond simple cases. In this book, I learned how to actually deploy a model as a web application. Great examples!
Amazon Verified review Amazon
Carlos en Urbana Mar 12, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a great book to really understand predictive analytics. Unlike other books it is not only a list of algorithms, but a complete guide of all the stages in the process of using predictive analytics to solve problems. Going from problem understanding to deploying a usable neural network model for a final user was really awesome!
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.