| 000 | 02570cam a2200277zu 4500 | ||
|---|---|---|---|
| 001 | 88865451 | ||
| 003 | FRCYB88865451 | ||
| 005 | 20250107231500.0 | ||
| 006 | m o d | ||
| 007 | cr un | ||
| 008 | 250108s2018 fr | o|||||0|0|||eng d | ||
| 020 | _a9781789801651 | ||
| 035 | _aFRCYB88865451 | ||
| 040 |
_aFR-PaCSA _ben _c _erda |
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| 100 | 1 | _aNagy, Zsolt | |
| 245 | 0 | 1 |
_aArtificial Intelligence and Machine Learning Fundamentals _c['Nagy, Zsolt'] |
| 264 | 1 |
_bPackt Publishing _c2018 |
|
| 300 | _a p. | ||
| 336 |
_btxt _2rdacontent |
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| 337 |
_bc _2rdamdedia |
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| 338 |
_bc _2rdacarrier |
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| 650 | 0 | _a | |
| 700 | 0 | _aNagy, Zsolt | |
| 856 | 4 | 0 |
_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88865451 _qtext/html _a |
| 520 | _aCreate AI applications in Python and lay the foundations for your career in data science Key Features Practical examples that explain key machine learning algorithms Explore neural networks in detail with interesting examples Master core AI concepts with engaging activities Book Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learn Understand the importance, principles, and fields of AI Implement basic artificial intelligence concepts with Python Apply regression and classification concepts to real-world problems Perform predictive analysis using decision trees and random forests Carry out clustering using the k-means and mean shift algorithms Understand the fundamentals of deep learning via practical examples Who this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python). | ||
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_c71505 _d71505 |
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