Regression Analysis with Python (notice n° 65679)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03123cam a2200289zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88843080 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250107220057.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250107s2016 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781785286315 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88843080 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Massaron, Luca |
| 245 01 - TITLE STATEMENT | |
| Title | Regression Analysis with Python |
| Statement of responsibility, etc. | ['Massaron, Luca', 'Boschetti, Alberto'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Packt Publishing |
| Date of production, publication, distribution, manufacture, or copyright notice | 2016 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Learn the art of regression analysis with PythonAbout This BookBecome competent at implementing regression analysis in PythonSolve some of the complex data science problems related to predicting outcomesGet to grips with various types of regression for effective data analysisWho This Book Is ForThe book targets Python developers, with a basic understanding of data science, statistics, and math, who want to learn how to do regression analysis on a dataset. It is beneficial if you have some knowledge of statistics and data science.What You Will LearnFormat a dataset for regression and evaluate its performanceApply multiple linear regression to real-world problemsLearn to classify training pointsCreate an observation matrix, using different techniques of data analysis and cleaningApply several techniques to decrease (and eventually fix) any overfitting problemLearn to scale linear models to a big dataset and deal with incremental dataIn DetailRegression is the process of learning relationships between inputs and continuous outputs from example data, which enables predictions for novel inputs. There are many kinds of regression algorithms, and the aim of this book is to explain which is the right one to use for each set of problems and how to prepare real-world data for it. With this book you will learn to define a simple regression problem and evaluate its performance. The book will help you understand how to properly parse a dataset, clean it, and create an output matrix optimally built for regression. You will begin with a simple regression algorithm to solve some data science problems and then progress to more complex algorithms. The book will enable you to use regression models to predict outcomes and take critical business decisions. Through the book, you will gain knowledge to use Python for building fast better linear models and to apply the results in Python or in any computer language you prefer.Style and approach This is a practical tutorial-based book. You will be given an example problem and then supplied with the relevant code and how to walk through it. The details are provided in a step by step manner, followed by a thorough explanation of the math underlying the solution. This approach will help you leverage your own data using the same techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Massaron, Luca |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Boschetti, Alberto |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88843080">https://international.scholarvox.com/netsen/book/88843080</a> |
| Electronic format type | text/html |
| Host name | |
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