Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Applied Data Science with Python and Jupyter
Applied Data Science with Python and Jupyter

Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data

eBook
$25.99
Paperback
$32.99
Subscription
Free Trial
Renews at $19.99p/m

What do you get with Print?

Product feature icon Instant access to your digital eBook copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Table of content icon View table of contents Preview book icon Preview Book

Applied Data Science with Python and Jupyter

Introduction


Consider a small food-delivery business that is looking to optimize their product. An analyst might look at the appropriate data and determine what type of food people are enjoying most. Perhaps they find a large amount of people are ordering the spiciest food options, indicating the business might be losing out on customers who desire something even more spicy. This is quite basic, or as some might say, "vanilla" analytics.

In a separate task, the analyst could employ predictive analytics by modeling the order volumes over time. With enough data, they could predict the future order volumes and therefore guide the restaurant as to how many staff are required each day. This model could take factors such as the weather into account to make the best predictions. For instance, a heavy rainstorm could be an indicator to staff more delivery personnel to make up for slow travel times. With historical weather data, that type of signal could be encoded into the model. This prediction...

Preparing to Train a Predictive Model


Here, we will cover the preparation required to train a predictive model. Although not as technically glamorous as training the models themselves, this step should not be taken lightly. It's very important to ensure you have a good plan before proceeding with the details of building and training a reliable model. Furthermore, once you've decided on the right plan, there are technical steps in preparing the data for modeling that should not be overlooked.

Note

We must be careful not to go so deep into the weeds of technical tasks that we lose sight of the goal. Technical tasks include things that require programming skills, for example, constructing visualizations, querying databases, and validating predictive models. It's easy to spend hours trying to implement a specific feature or get the plots looking just right. Doing this sort of thing is certainly beneficial to our programming skills, but we should not forget to ask ourselves if it's really worth...

Training Classification Models


As you've already seen in the previous chapter, using libraries such as scikit-learn and platforms such as Jupyter, predictive models can be trained in just a few lines of code. This is possible by abstracting away the difficult computations involved with optimizing model parameters. In other words, we deal with a black box where the internal operations are hidden instead. With this simplicity also comes the danger of misusing algorithms, for example, by overfitting during training or failing to properly test on unseen data. We'll show how to avoid these pitfalls while training classification models and produce trustworthy results with the use of k-fold cross validation and validation curves.

Introduction to Classification Algorithms

Recall the two types of supervised machine learning: regression and classification. In regression, we predict a continuous target variable. For example, recall the linear and polynomial models from the first chapter. In this chapter...

Summary


In this chapter, we have seen how predictive models can be trained in Jupyter Notebooks.

To begin with, we talked about how to plan a machine learning strategy. We thought about how to design a plan that can lead to actionable business insights and stressed the importance of using the data to help set realistic business goals. We also explained machine learning terminology such as supervised learning, unsupervised learning, classification, and regression.

Next, we discussed methods for preprocessing data using scikit-learn and pandas. This included lengthy discussions and examples of a surprisingly time-consuming part of machine learning: dealing with missing data.

In the latter half of the chapter, we trained predictive classification models for our binary problem, comparing how decision boundaries are drawn for various models such as the SVM, k-Nearest Neighbors, and Random Forest. We then showed how validation curves can be used to make good parameter choices and how dimensionality...

Summary

In this chapter, we have seen how predictive models can be trained in Jupyter Notebooks.

To begin with, we talked about how to plan a machine learning strategy. We thought about how to design a plan that can lead to actionable business insights and stressed the importance of using the data to help set realistic business goals. We also explained machine learning terminology such as supervised learning, unsupervised learning, classification, and regression.

Next, we discussed methods for preprocessing data using scikit-learn and pandas. This included lengthy discussions and examples of a surprisingly time-consuming part of machine learning: dealing with missing data.

In the latter half of the chapter, we trained predictive classification models for our binary problem, comparing how decision boundaries are drawn for various models such as the SVM, k-Nearest Neighbors, and Random Forest. We then showed how validation curves can be used to make good parameter choices...

Left arrow icon Right arrow icon

Key benefits

  • Get up and running with the Jupyter ecosystem and some example datasets
  • Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests
  • Discover how you can use web scraping to gather and parse your own bespoke datasets

Description

Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.

Who is this book for?

Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.

What you will learn

  • Get up and running with the Jupyter ecosystem
  • Identify potential areas of investigation and perform exploratory data analysis
  • Plan a machine learning classification strategy and train classification models
  • Use validation curves and dimensionality reduction to tune and enhance your models
  • Scrape tabular data from web pages and transform it into Pandas DataFrames
  • Create interactive, web-friendly visualizations to clearly communicate your findings
Estimated delivery fee Deliver to South Korea

Standard delivery 10 - 13 business days

$12.95

Premium delivery 5 - 8 business days

$45.95
(Includes tracking information)

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2018
Length: 192 pages
Edition : 1st
Language : English
ISBN-13 : 9781789958171
Category :
Languages :
Concepts :
Tools :

What do you get with Print?

Product feature icon Instant access to your digital eBook copy whilst your Print order is Shipped
Product feature icon Paperback book shipped to your preferred address
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Estimated delivery fee Deliver to South Korea

Standard delivery 10 - 13 business days

$12.95

Premium delivery 5 - 8 business days

$45.95
(Includes tracking information)

Product Details

Publication date : Oct 31, 2018
Length: 192 pages
Edition : 1st
Language : English
ISBN-13 : 9781789958171
Category :
Languages :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 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
$199.99 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
$279.99 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 $ 109.97
Data Science Algorithms in a Week
$43.99
Artificial Intelligence and Machine Learning Fundamentals
$32.99
Applied Data Science with Python and Jupyter
$32.99
Total $ 109.97 Stars icon

Table of Contents

3 Chapters
Jupyter Fundamentals Chevron down icon Chevron up icon
Data Cleaning and Advanced Machine Learning Chevron down icon Chevron up icon
Web Scraping and Interactive Visualizations Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3
(3 Ratings)
5 star 66.7%
4 star 0%
3 star 33.3%
2 star 0%
1 star 0%
Lukas K. Aug 09, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Although this book only covers some of the techniques and approaches usually encountered when reading about data sciences, it covers them really well. And it has a clear structure. I especially liked the broad coverage on Jupyter at the beginning of the book. I can recommend this book to everyone that wants to get into the field of data science. You definitely, need some further material, but it certainly adds knowledge and value.
Amazon Verified review Amazon
wPastor Mar 01, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The iBook version contain blurred images for that reason I bought the paper version.The book is perfect for me as a new guy in data science. The author teachs how to install anaconda and how to uptodate it's libraries. Shows how to work with jupyter notebooks and analize libraries such as pandas, matplotlib, numpy, etc.Excellent book to learn how to clean up data and show the results you are looking for.
Amazon Verified review Amazon
kia Feb 08, 2019
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
I just purchased the book online. Some of the code examples are so blurred that are unreadable
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 the delivery time and cost of print book? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela
What is custom duty/charge? Chevron down icon Chevron up icon

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order? Chevron down icon Chevron up icon

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges? Chevron down icon Chevron up icon

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

  • If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
  • Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.
How can I cancel my order? Chevron down icon Chevron up icon

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy? Chevron down icon Chevron up icon

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

  1. If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
  2. Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
  3. You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
  4. Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
  5. If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
  6. Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged? Chevron down icon Chevron up icon

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use? Chevron down icon Chevron up icon

You can pay with the following card types:

  1. Visa Debit
  2. Visa Credit
  3. MasterCard
  4. PayPal
What is the delivery time and cost of print books? Chevron down icon Chevron up icon

Shipping Details

USA:

'

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.


Unfortunately, due to several restrictions, we are unable to ship to the following countries:

  1. Afghanistan
  2. American Samoa
  3. Belarus
  4. Brunei Darussalam
  5. Central African Republic
  6. The Democratic Republic of Congo
  7. Eritrea
  8. Guinea-bissau
  9. Iran
  10. Lebanon
  11. Libiya Arab Jamahriya
  12. Somalia
  13. Sudan
  14. Russian Federation
  15. Syrian Arab Republic
  16. Ukraine
  17. Venezuela