MATLAB Machine Learning Recipes: A Problem-Solution Approach
Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular pr...
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Berkeley, CA
Apress L. P.
2024
|
| Ausgabe: | 3rd ed. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781484298466/?ar |
| Zusammenfassung: | Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists. |
| Beschreibung: | Description based upon print version of record. - 4.4 Using the UKF for State Estimation |
| Umfang: | 1 Online-Ressource (458 Seiten) |
| ISBN: | 9781484298466 1484298462 |
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| spelling | Paluszek, Michael VerfasserIn aut MATLAB Machine Learning Recipes A Problem-Solution Approach Michael Paluszek, Stephanie Thomas 3rd ed. Berkeley, CA Apress L. P. 2024 1 Online-Ressource (458 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Description based upon print version of record. - 4.4 Using the UKF for State Estimation Harness the power of MATLAB to resolve a wide range of machine learning challenges. This new and updated third edition provides examples of technologies critical to machine learning. Each example solves a real-world problem, and all code provided is executable. You can easily look up a particular problem and follow the steps in the solution. This book has something for everyone interested in machine learning. It also has material that will allow those with an interest in other technology areas to see how machine learning and MATLAB can help them solve problems in their areas of expertise. The chapter on data representation and MATLAB graphics includes new data types and additional graphics. Chapters on fuzzy logic, simple neural nets, and autonomous driving have new examples added. And there is a new chapter on spacecraft attitude determination using neural nets. Authors Michael Paluszek and Stephanie Thomas show how all of these technologies allow you to build sophisticated applications to solve problems with pattern recognition, autonomous driving, expert systems, and much more. What You Will Learn Write code for machine learning, adaptive control, and estimation using MATLAB Use MATLAB graphics and visualization tools for machine learning Become familiar with neural nets Build expert systems Understand adaptive control Gain knowledge of Kalman Filters Who This Book Is For Software engineers, control engineers, university faculty, undergraduate and graduate students, hobbyists. MATLAB Machine learning Apprentissage automatique Thomas, Stephanie VerfasserIn aut 9781484298459 Erscheint auch als Druck-Ausgabe 9781484298459 |
| spellingShingle | Paluszek, Michael Thomas, Stephanie MATLAB Machine Learning Recipes A Problem-Solution Approach MATLAB Machine learning Apprentissage automatique |
| title | MATLAB Machine Learning Recipes A Problem-Solution Approach |
| title_auth | MATLAB Machine Learning Recipes A Problem-Solution Approach |
| title_exact_search | MATLAB Machine Learning Recipes A Problem-Solution Approach |
| title_full | MATLAB Machine Learning Recipes A Problem-Solution Approach Michael Paluszek, Stephanie Thomas |
| title_fullStr | MATLAB Machine Learning Recipes A Problem-Solution Approach Michael Paluszek, Stephanie Thomas |
| title_full_unstemmed | MATLAB Machine Learning Recipes A Problem-Solution Approach Michael Paluszek, Stephanie Thomas |
| title_short | MATLAB Machine Learning Recipes |
| title_sort | matlab machine learning recipes a problem solution approach |
| title_sub | A Problem-Solution Approach |
| topic | MATLAB Machine learning Apprentissage automatique |
| topic_facet | MATLAB Machine learning Apprentissage automatique |
| work_keys_str_mv | AT paluszekmichael matlabmachinelearningrecipesaproblemsolutionapproach AT thomasstephanie matlabmachinelearningrecipesaproblemsolutionapproach |