By Gavin Hackeling
Apply potent studying algorithms to real-world difficulties utilizing scikit-learn
About This Book
• layout and troubleshoot laptop studying structures for universal projects together with regression, category, and clustering
• Acquaint your self with renowned laptop studying algorithms, together with selection bushes, logistic regression, and aid vector machines
• a realistic example-based advisor that can assist you achieve services in enforcing and comparing laptop studying platforms utilizing scikit-learn
[ Who This publication Is For
If you're a software program developer who desires to find out how computing device studying versions paintings and the way to use them successfully, this ebook is for you. Familiarity with computing device studying basics and Python can be useful, yet isn't really crucial.
What you are going to study
• overview basic suggestions together with supervised and unsupervised studies, universal projects, and function metrics
• are expecting the values of continuing variables utilizing linear regression
• Create representations of files and pictures that may be utilized in laptop studying types
• Categorize records and textual content messages utilizing logistic regression and help vector machines
• Classify pictures by way of their matters
• observe hidden constructions in information utilizing clustering and visualize complicated facts utilizing decomposition
• overview the functionality of desktop studying structures in universal projects
• Diagnose and redress issues of versions as a result of bias and variance
This ebook examines computing device studying versions together with logistic regression, selection timber, and aid vector machines, and applies them to universal difficulties comparable to categorizing records and classifying pictures. It starts with the basics of desktop studying, introducing you to the supervised-unsupervised spectrum, the makes use of of teaching and attempt info, and comparing versions. you'll how you can use generalized linear versions in regression difficulties, in addition to clear up issues of textual content and specific features.
You can be familiar with using logistic regression, regularization, and many of the loss capabilities which are utilized by generalized linear types. The booklet also will stroll you thru an instance undertaking that activates you to label the main doubtful education examples. additionally, you will use an unmanaged Hidden Markov version to foretell inventory prices.
By the top of the booklet, you may be a professional in scikit-learn and should be good versed in laptop studying
Read or Download Mastering Machine Learning with scikit-learn PDF
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Additional resources for Mastering Machine Learning with scikit-learn
A section, if provided, will direct man to look only in that sec tion of the manual. The default action is to search in all of the available sections, following a pre-defined order and to show only the first page found, even if page exists in several sections.
Take some time to explore the man page of a command we’ve discussed or of another command or program you know of. Learn about a couple of new arguments or options and try them out. Practice killing or interrupting programs if neces‐ sary. Now that this chapter has touched on the various commands for running processes and manipulating files, let’s see how those commands can be combined into powerful pipelines using redirection and pipes. Combining Utilities with Redirection and Pipes (>, >>, and |) The power of the shell lies in the ability to combine these simple utilities into more complex algorithms very quickly.
Exercise: Find Home 1. Open the Terminal. 2. Type pwd at the command prompt and press Enter to see the absolute path to your home directory. Now that she knows where she is in the filesystem, curious Lise is interested in what she’ll find there. To list the contents of a directory, she’ll need the ls command. Listing the Contents (ls) The ls command allows the user to print out a list of all the files and subdirectories in a directory. Exercise: List the Contents of a Directory 1. Open the Terminal.