Python: Deeper Insights into Machine Learning (notice n° 65947)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03768cam a2200301zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88843350 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250107220400.0 |
| 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 | 9781787128576 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88843350 |
| 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 | Raschka, Sebastian |
| 245 01 - TITLE STATEMENT | |
| Title | Python: Deeper Insights into Machine Learning |
| Statement of responsibility, etc. | ['Raschka, Sebastian', 'Julian, David', 'Hearty, John'] |
| 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. | Leverage benefits of machine learning techniques using PythonAbout This BookImprove and optimise machine learning systems using effective strategies.Develop a strategy to deal with a large amount of data.Use of Python code for implementing a range of machine learning algorithms and techniques.Who This Book Is ForThis title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts.What You Will LearnLearn to write clean and elegant Python code that will optimize the strength of your algorithmsUncover hidden patterns and structures in data with clusteringImprove accuracy and consistency of results using powerful feature engineering techniquesGain practical and theoretical understanding of cutting-edge deep learning algorithmsSolve unique tasks by building modelsGet grips on the machine learning design processIn DetailMachine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project.The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems.The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems.At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering.Style and approachThis course includes all the resources that will help you jump into the data science field with Python. The aim is to walk through the elements of Python covering powerful machine learning libraries. This course will explain important machine learning models in a step-by-step manner. Each topic is well explained with real-world applications with detailed guidance.Through this comprehensive guide, you will be able to explore machine learning techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Raschka, Sebastian |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Julian, David |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hearty, John |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88843350">https://international.scholarvox.com/netsen/book/88843350</a> |
| Electronic format type | text/html |
| Host name | |
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