Python Machine Learning for Beginners: All You Need to Know about Machine Learning with Python
- Autor
- Narrador
- Editorial
- Ediciones
3
- 2 calificaciones
4
- Duración
- 1 h 27 m
- Idioma
- Inglés
- Formato
- Categoría
No ficción
Have you thought about a career in data science? It's where the money is right now, and it's only going to become more widespread as the world evolves. Machine learning is a big part of data science, and for those that already have experience in programming, it's the next logical step.
Machine learning is a subsection of AI, or Artificial Intelligence, and computer science, using data and algorithms to imitate human thinking and learning. Through constant learning, machine learning gradually improves its accuracy, eventually providing the optimal results for the problem it has been assigned to.
It is one of the most important parts of data science and, as big data continues to expand, so too will the need for machine learning and AI.
Here's what you will learn in this quick guide to machine learning with Python for beginners:
What machine learning isWhy Python is the best computer programming language for machine learningThe different types of machine learningHow linear regression worksThe different types of classificationHow to use SVMs (Support Vector Machines) with Scikit-LearnHow Decision Trees work with ClassificationHow K-Nearest Neighbors worksHow to find patterns in data with unsupervised learning algorithms
You will also find plenty of code examples to help you understand how everything works.
If you are ready to take your programming further, scroll up, click Buy Now, and find out why machine learning is the next logical step.
© 2022 Alex Published (Audiolibro): 9781669682929
Fecha de lanzamiento
Audiolibro: 21 de abril de 2022
Otras ediciones
Otros también disfrutaron...
- The Science of Genius Scientific American
- Generative Artificial Intelligence for Beginners: Generative Artificial Intelligence for Beginners SAM CAMPBELL
- Bitcoin Cryptocurrency Blockchain Cecil (CJ) John
- Incident Response Masterclass: Navigate and Resolve Cyber Threats with Digital Forensics Expertise Virversity Online Courses
- The Science of Education: Back to School Scientific American
- Digital Finance: Security Tokens and Unlocking the Real Potential of Blockchain Baxter Hines
- Talent Tectonics: Navigating Global Workforce Shifts, Building Resilient Organizations and Reimagining the Employee Experience Steven T. Hunt
- Powering Prosperity: A Citizen's Guide to Shaping the 21st Century Indranil Ghosh
- The Mystery of Sleep Scientific American
- Connect Using Humor and Story: How I Got 18 Laughs 3 Applauses in a 7 Minute Persuasive Speech Ramakrishna Reddy
- The CISO Evolution: Business Knowledge for Cybersecurity Executives Kyriakos Lambros, Matthew K. Sharp
- Supercharged Supply Chains: Discover Unparalleled Business Planning and Execution Practices James Bentzley, James G. Correll, Lloyd C. Snowden
- DeFi For Dummies Seoyoung Kim
- Comerás flores Lucía Solla Sobral
- Yesteryear Caro Claire Burke
- La Biblioteca de la Medianoche (AdN) Matt Haig
- La mala hija Pedro Martí
- Llevará tu nombre Sonsoles Ónega
- La novia gitana (Inspectora Elena Blanco 1) Carmen Mola
- El club de las indomables: Por la autora de Criadas y señoras Kathryn Stockett
- Zodiac Academy 1. El despertar Susanne Valenti, Caroline Peckham
- El verano en que mi madre tuvo los ojos verdes Tatiana Tibuleac, Tatiana Ţîbuleac
- El baile de las criadas: Premio de Novela Fernando Lara 2026 Marta Platel
- Con amor, mamá: El thriller más viral del año, que se ha convertido en un fenómeno global Iliana Xander
- Lady Mayfield Julie Klassen
- Yo que nunca supe de los hombres Jacqueline Harpman
- Malditos Arturo del Burgo
- 25 últimos veranos Stephan Schäfer
Explora nuevos mundos
Más de 1 millón de títulos
Modo sin conexión
Kids Mode
Cancela en cualquier momento
Unlimited
Historias ilimitadas que te ayudarán a pausar y a inspirarte.
$7.99 /mes
1 cuenta
Acceso ilimitado
Escucha y lee los títulos que quieras
Modo sin conexión + Modo Infantil
Cancela en cualquier momento
