Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
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
Practical Machine Learning Cookbook
Practical Machine Learning Cookbook

Practical Machine Learning Cookbook: Supervised and unsupervised machine learning simplified

eBook
€8.99 €39.99
Paperback
€49.99
Subscription
Free Trial
Renews at €18.99p/m

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
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
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Table of content icon View table of contents Preview book icon Preview Book

Practical Machine Learning Cookbook

Discriminant function analysis - geological measurements on brines from wells


Let us assume that a study of ancient artifacts that have been collected from mines needs to be carried out. Rock samples have been collected from the mines. On the collected rock samples geochemical measurements have been carried out. A similar study has been carried out on the collected artifacts. In order to separate the samples into the mine from which they were excavated, DFA can be used as a function. The function can then be applied to the artifacts to predict which mine was the source of each artifact.

Getting ready

In order to perform discriminant function analysis we shall be using a dataset collected from mines.

Step 1 - collecting and describing data

The dataset on data analysis in geology titled BRINE shall be used. This can be obtained from http://www.kgs.ku.edu/Mathgeo/Books/Stat/ASCII/BRINE.TXT . The dataset is in a standard form, with rows corresponding to samples and columns corresponding to variables...

Multinomial logistic regression - understanding program choices made by students


Let's assume that high school students are to be enrolled on a program. The students are given the opportunity to choose programs of their choice. The choices of the students are based on three options. These choices are general program, vocational program, and academic program. The choice of each student is based on each student's writing score and social economic status.

Getting ready

In order to complete this recipe we shall be using a student's dataset. The first step is collecting the data.

Step 1 - collecting data

The student's dataset titled hsbdemo is being utilized. The dataset is available at: http://voia.yolasite.com/resources/hsbdemo.csv in an MS Excel format. There are 201 data rows and 13 variables in the dataset. The eight numeric measurements are as follows:

  • id
  • read
  • write
  • math
  • science
  • socst
  • awards
  • cid

The non-numeric measurements are as follows:

  • gender
  • ses
  • schtyp
  • prog
  • honors

How to do it...

Let's get into the...

Tobit regression - measuring the students' academic aptitude


Let us measure the academic aptitude of a student on a scale of 200-800. This measurement is based on the model using reading and math scores. The nature of the program in which the student has been enrolled is also to be taken into consideration. There are three types of programs: academic, general, and vocational. The problem is that some students may answer all the questions on the academic aptitude test correctly and score 800 even though it is likely that these students are not truly equal in aptitude. This may be true for all the students who may answer all the questions incorrectly and score 200.

Getting ready

In order to complete this recipe we shall be using a student's dataset. The first step is collecting the data.

Step 1 - collecting data

To develop the Tobit regression model we shall use the student dataset titled tobit, which is available at http://www.ats.ucla.edu/stat/data/tobit.csv in an MS Excel format. There are...

Poisson regression - understanding species present in Galapagos Islands


The Galapagos Islands are situated in the Pacific Ocean about 1000 km from the Ecuadorian coast. The archipelago consists of 13 islands, five of which are inhabited. The islands are rich in flora and fauna. Scientists are still perplexed by the fact that such a diverse set of species can flourish in such a small and remote group of islands.

Getting ready

In order to complete this recipe we shall be using species dataset. The first step is collecting the data.

Step 1 - collecting and describing the data

We will utilize the number of species dataset titled gala that is available at https://github.com/burakbayramli/kod/blob/master/books/Practical_Regression_Anove_Using_R_Faraway/gala.txt .

The dataset includes 30 cases and seven variables in the dataset. The seven numeric measurements include the following:

  • Species
  • Endemics
  • Area
  • Elevation
  • Nearest
  • Scruz
  • Adjcacent

How to do it...

Let's get into the details.

Step 2 - exploring the data...

Tobit regression - measuring the students' academic aptitude

Let us measure the academic aptitude of a student on a scale of 200-800. This measurement is based on the model using reading and math scores. The nature of the program in which the student has been enrolled is also to be taken into consideration. There are three types of programs: academic, general, and vocational. The problem is that some students may answer all the questions on the academic aptitude test correctly and score 800 even though it is likely that these students are not truly equal in aptitude. This may be true for all the students who may answer all the questions incorrectly and score 200.

Getting ready

In order to complete this recipe we shall be using a student's dataset. The first step is collecting the data.

Step 1 - collecting data

To develop the Tobit regression model we shall use the student dataset titled tobit, which is available at http://www.ats.ucla.edu/stat/data/tobit.csv in an MS Excel format...

Poisson regression - understanding species present in Galapagos Islands

The Galapagos Islands are situated in the Pacific Ocean about 1000 km from the Ecuadorian coast. The archipelago consists of 13 islands, five of which are inhabited. The islands are rich in flora and fauna. Scientists are still perplexed by the fact that such a diverse set of species can flourish in such a small and remote group of islands.

Getting ready

In order to complete this recipe we shall be using species dataset. The first step is collecting the data.

Step 1 - collecting and describing the data

We will utilize the number of species dataset titled gala that is available at https://github.com/burakbayramli/kod/blob/master/books/Practical_Regression_Anove_Using_R_Faraway/gala.txt .

The dataset includes 30 cases and seven variables in the dataset. The seven numeric measurements include the following:

  • Species
  • Endemics
  • Area
  • Elevation
  • Nearest
  • Scruz
  • Adjcacent

How to do it...

Let's get into the details.

Step 2 - exploring the...

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • • Implement a wide range of algorithms and techniques for tackling complex data
  • • Improve predictions and recommendations to have better levels of accuracy
  • • Optimize performance of your machine-learning systems

Description

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations. The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more. The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.

Who is this book for?

This book is for analysts, statisticians, and data scientists with knowledge of fundamentals of machine learning and statistics, who need help in dealing with challenging scenarios faced every day of working in the field of machine learning and improving system performance and accuracy. It is assumed that as a reader you have a good understanding of mathematics. Working knowledge of R is expected.

What you will learn

  • Get equipped with a deeper understanding of how to apply machine-learning techniques
  • Implement each of the advanced machine-learning techniques
  • Solve real-life problems that are encountered in order to make your applications produce improved results
  • Gain hands-on experience in problem solving for your machine-learning systems
  • Understand the methods of collecting data, preparing data for usage, training the model, evaluating the model's performance, and improving the model's performance

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 14, 2017
Length: 570 pages
Edition : 1st
Language : English
ISBN-13 : 9781785286537
Vendor :
Amazon
Category :
Languages :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
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
OR
Modal Close icon
Payment Processing...
tick Completed

Billing Address

Product Details

Publication date : Apr 14, 2017
Length: 570 pages
Edition : 1st
Language : English
ISBN-13 : 9781785286537
Vendor :
Amazon
Category :
Languages :

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 128.97
Practical Machine Learning Cookbook
€49.99
Machine Learning for Developers
€36.99
Machine Learning Algorithms
€41.99
Total 128.97 Stars icon
Banner background image

Table of Contents

14 Chapters
1. Introduction to Machine Learning Chevron down icon Chevron up icon
2. Classification Chevron down icon Chevron up icon
3. Clustering Chevron down icon Chevron up icon
4. Model Selection and Regularization Chevron down icon Chevron up icon
5. Nonlinearity Chevron down icon Chevron up icon
6. Supervised Learning Chevron down icon Chevron up icon
7. Unsupervised Learning Chevron down icon Chevron up icon
8. Reinforcement Learning Chevron down icon Chevron up icon
9. Structured Prediction Chevron down icon Chevron up icon
10. Neural Networks Chevron down icon Chevron up icon
11. Deep Learning Chevron down icon Chevron up icon
12. Case Study - Exploring World Bank Data Chevron down icon Chevron up icon
13. Case Study - Pricing Reinsurance Contracts Chevron down icon Chevron up icon
14. Case Study - Forecast of Electricity Consumption Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(1 Ratings)
5 star 0%
4 star 0%
3 star 100%
2 star 0%
1 star 0%
Ram Jun 12, 2017
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
So far explanations are not easy to understand & steps are skipped.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.