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Sprache:
Englisch
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Beschreibung
Master the algorithms powering today's AI revolution. This practical guide breaks down the foundations of machine learning into clear, structured lessons-covering supervised learning, unsupervised learning, and reinforcement learning.
Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally.
This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development.
If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally.
This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development.
If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Master the algorithms powering today's AI revolution. This practical guide breaks down the foundations of machine learning into clear, structured lessons-covering supervised learning, unsupervised learning, and reinforcement learning.
Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally.
This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development.
If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally.
This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development.
If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Über den Autor
E. Jarrel is a college teacher who teaches computer programming courses . He has been writing programs since he was 15 years old. Jarrel currently focuses on writing software that addresses inefficiencies in education and brings the benefits of open source software to the field of education. In his spare time he enjoys climbing mountains and spending time with his family.
Details
Erscheinungsjahr: | 2025 |
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Genre: | Importe, Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
ISBN-13: | 9798231376452 |
Sprache: | Englisch |
Einband: | Kartoniert / Broschiert |
Autor: | E., Jarrel |
Hersteller: | Jarrel E. |
Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
Maße: | 280 x 216 x 13 mm |
Von/Mit: | Jarrel E. |
Erscheinungsdatum: | 09.05.2025 |
Gewicht: | 0,595 kg |