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:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Berkeley, CA
Apress
2024
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| Ausgabe: | third edition |
| Schlagworte: | |
| Online-Zugang: | DE-522 DE-1043 DE-1046 DE-Aug4 DE-1050 DE-573 DE-M347 DE-92 DE-1051 DE-898 DE-860 DE-1049 DE-863 DE-862 DE-523 DE-20 DE-706 URL des Erstveröffentlichers |
| 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: | 1 Online-Ressource (XXIII, 447 Seiten) Diagramme |
| ISBN: | 9781484298466 |
| DOI: | 10.1007/978-1-4842-9846-6 |
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| contents | Intro -- Contents -- About the Authors -- About the Technical Reviewer -- Introduction -- 1 An Overview of Machine Learning -- 1.1 Introduction -- 1.2 Elements of Machine Learning -- 1.2.1 Data -- 1.2.2 Models -- 1.2.3 Training -- Supervised Learning -- Unsupervised Learning -- Semi-supervised Learning -- Online Learning -- 1.3 The Learning Machine -- 1.4 Taxonomy of Machine Learning -- 1.5 Control -- 1.5.1 Kalman Filters -- 1.5.2 Adaptive Control -- 1.6 Autonomous Learning Methods -- 1.6.1 Regression -- 1.6.2 Decision Trees -- 1.6.3 Neural Networks -- Introduction -- Generative Deep Learning Reinforcement Learning -- 1.6.4 Support Vector Machines (SVMs) -- 1.7 Artificial Intelligence -- 1.7.1 What Is Artificial Intelligence? -- 1.7.2 Intelligent Cars -- 1.7.3 Expert Systems -- 1.8 Summary -- 2 Data for Machine Learning in MATLAB -- 2.1 Introduction to MATLAB Data Types -- 2.1.1 Matrices -- 2.1.2 Cell Arrays -- 2.1.3 Data Structures -- 2.1.4 Numerics -- 2.1.5 Images -- 2.1.6 Datastore -- 2.1.7 Tall Arrays -- 2.1.8 Sparse Matrices -- 2.1.9 Tables and Categoricals -- 2.1.10 Large MAT-Files -- 2.2 Initializing a Data Structure -- 2.2.1 Problem -- 2.2.2 Solution -- 2.2.3 How It Works 2.3 mapreduce on an Image Datastore -- 2.3.1 Problem -- 2.3.2 Solution -- 2.3.3 How It Works -- 2.4 Processing Table Data -- 2.4.1 Problem -- 2.4.2 Solution -- 2.4.3 How It Works -- 2.5 String Concatenation -- 2.5.1 Problem -- 2.5.2 Solution -- 2.5.3 How It Works -- 2.6 Arrays of Strings -- 2.6.1 Problem -- 2.6.2 Solution -- 2.6.3 How It Works -- 2.7 Substrings -- 2.7.1 Problem -- 2.7.2 Solution -- 2.7.3 How It Works -- 2.8 Reading an Excel Spreadsheet into a Table -- 2.8.1 Problem -- 2.8.2 Solution -- 2.8.3 How It Works -- 2.9 Accessing ChatGPT -- 2.9.1 Problem -- 2.9.2 Solution 2.9.3 How It Works -- 2.10 Summary -- 3 MATLAB Graphics -- 3.1 2D Line Plots -- 3.1.1 Problem -- 3.1.2 Solution -- 3.1.3 How It Works -- 3.2 General 2D Graphics -- 3.2.1 Problem -- 3.2.2 Solution -- 3.2.3 How It Works -- 3.3 Custom Two-Dimensional Diagrams -- 3.3.1 Problem -- 3.3.2 Solution -- 3.3.3 How It Works -- 3.4 Three-Dimensional Box -- 3.4.1 Problem -- 3.4.2 Solution -- 3.4.3 How It Works -- 3.5 Draw a 3D Object with a Texture -- 3.5.1 Problem -- 3.5.2 Solution -- 3.5.3 How It Works -- 3.6 General 3D Graphics -- 3.6.1 Problem -- 3.6.2 Solution -- 3.6.3 How It Works -- 3.7 Building a GUI 3.7.1 Problem -- 3.7.2 Solution -- 3.7.3 How It Works -- 3.8 Animating a Bar Chart -- 3.8.1 Problem -- 3.8.2 Solution -- 3.8.3 How It Works -- 3.9 Drawing a Robot -- 3.9.1 Problem -- 3.9.2 Solution -- 3.9.3 How It Works -- 3.10 Importing a Model -- 3.10.1 Problem -- 3.10.2 Solution -- 3.10.3 How It Works -- 3.11 Summary -- 4 Kalman Filters -- 4.1 Gaussian Distribution -- 4.2 A State Estimator Using a Linear Kalman Filter -- 4.2.1 Problem -- 4.2.2 Solution -- 4.2.3 How It Works -- 4.3 Using the Extended Kalman Filter for State Estimation -- 4.3.1 Problem -- 4.3.2 Solution -- 4.3.3 How It Works |
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| discipline | Informatik |
| doi_str_mv | 10.1007/978-1-4842-9846-6 |
| edition | third edition |
| format | Electronic eBook |
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| id | DE-604.BV049639283 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:39:18Z |
| indexdate | 2024-12-29T04:02:04Z |
| institution | BVB |
| isbn | 9781484298466 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034982933 |
| oclc_num | 1429567134 |
| open_access_boolean | |
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| owner_facet | DE-1043 DE-1046 DE-Aug4 DE-1050 DE-573 DE-M347 DE-92 DE-1051 DE-898 DE-BY-UBR DE-860 DE-1049 DE-863 DE-BY-FWS DE-862 DE-BY-FWS DE-523 DE-20 DE-706 DE-522 |
| physical | 1 Online-Ressource (XXIII, 447 Seiten) Diagramme |
| psigel | ZDB-2-CWD ZDB-2-CWD_2024 |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | Apress |
| record_format | marc |
| spellingShingle | Paluszek, Michael 1954- MATLAB machine learning recipes a problem-solution approach Intro -- Contents -- About the Authors -- About the Technical Reviewer -- Introduction -- 1 An Overview of Machine Learning -- 1.1 Introduction -- 1.2 Elements of Machine Learning -- 1.2.1 Data -- 1.2.2 Models -- 1.2.3 Training -- Supervised Learning -- Unsupervised Learning -- Semi-supervised Learning -- Online Learning -- 1.3 The Learning Machine -- 1.4 Taxonomy of Machine Learning -- 1.5 Control -- 1.5.1 Kalman Filters -- 1.5.2 Adaptive Control -- 1.6 Autonomous Learning Methods -- 1.6.1 Regression -- 1.6.2 Decision Trees -- 1.6.3 Neural Networks -- Introduction -- Generative Deep Learning Reinforcement Learning -- 1.6.4 Support Vector Machines (SVMs) -- 1.7 Artificial Intelligence -- 1.7.1 What Is Artificial Intelligence? -- 1.7.2 Intelligent Cars -- 1.7.3 Expert Systems -- 1.8 Summary -- 2 Data for Machine Learning in MATLAB -- 2.1 Introduction to MATLAB Data Types -- 2.1.1 Matrices -- 2.1.2 Cell Arrays -- 2.1.3 Data Structures -- 2.1.4 Numerics -- 2.1.5 Images -- 2.1.6 Datastore -- 2.1.7 Tall Arrays -- 2.1.8 Sparse Matrices -- 2.1.9 Tables and Categoricals -- 2.1.10 Large MAT-Files -- 2.2 Initializing a Data Structure -- 2.2.1 Problem -- 2.2.2 Solution -- 2.2.3 How It Works 2.3 mapreduce on an Image Datastore -- 2.3.1 Problem -- 2.3.2 Solution -- 2.3.3 How It Works -- 2.4 Processing Table Data -- 2.4.1 Problem -- 2.4.2 Solution -- 2.4.3 How It Works -- 2.5 String Concatenation -- 2.5.1 Problem -- 2.5.2 Solution -- 2.5.3 How It Works -- 2.6 Arrays of Strings -- 2.6.1 Problem -- 2.6.2 Solution -- 2.6.3 How It Works -- 2.7 Substrings -- 2.7.1 Problem -- 2.7.2 Solution -- 2.7.3 How It Works -- 2.8 Reading an Excel Spreadsheet into a Table -- 2.8.1 Problem -- 2.8.2 Solution -- 2.8.3 How It Works -- 2.9 Accessing ChatGPT -- 2.9.1 Problem -- 2.9.2 Solution 2.9.3 How It Works -- 2.10 Summary -- 3 MATLAB Graphics -- 3.1 2D Line Plots -- 3.1.1 Problem -- 3.1.2 Solution -- 3.1.3 How It Works -- 3.2 General 2D Graphics -- 3.2.1 Problem -- 3.2.2 Solution -- 3.2.3 How It Works -- 3.3 Custom Two-Dimensional Diagrams -- 3.3.1 Problem -- 3.3.2 Solution -- 3.3.3 How It Works -- 3.4 Three-Dimensional Box -- 3.4.1 Problem -- 3.4.2 Solution -- 3.4.3 How It Works -- 3.5 Draw a 3D Object with a Texture -- 3.5.1 Problem -- 3.5.2 Solution -- 3.5.3 How It Works -- 3.6 General 3D Graphics -- 3.6.1 Problem -- 3.6.2 Solution -- 3.6.3 How It Works -- 3.7 Building a GUI 3.7.1 Problem -- 3.7.2 Solution -- 3.7.3 How It Works -- 3.8 Animating a Bar Chart -- 3.8.1 Problem -- 3.8.2 Solution -- 3.8.3 How It Works -- 3.9 Drawing a Robot -- 3.9.1 Problem -- 3.9.2 Solution -- 3.9.3 How It Works -- 3.10 Importing a Model -- 3.10.1 Problem -- 3.10.2 Solution -- 3.10.3 How It Works -- 3.11 Summary -- 4 Kalman Filters -- 4.1 Gaussian Distribution -- 4.2 A State Estimator Using a Linear Kalman Filter -- 4.2.1 Problem -- 4.2.2 Solution -- 4.2.3 How It Works -- 4.3 Using the Extended Kalman Filter for State Estimation -- 4.3.1 Problem -- 4.3.2 Solution -- 4.3.3 How It Works Artificial Intelligence Big Data Artificial intelligence Big data MATLAB (DE-588)4329066-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4329066-8 (DE-588)4193754-5 |
| 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_exact_search_txtP | 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 | Artificial Intelligence Big Data Artificial intelligence Big data MATLAB (DE-588)4329066-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Artificial Intelligence Big Data Artificial intelligence Big data MATLAB Maschinelles Lernen |
| url | https://doi.org/10.1007/978-1-4842-9846-6 |
| work_keys_str_mv | AT paluszekmichael matlabmachinelearningrecipesaproblemsolutionapproach AT thomasstephanie matlabmachinelearningrecipesaproblemsolutionapproach |