Understanding Machine Learning
Price: $66.99 - $54.11
(as of Dec 03,2024 16:35:14 UTC – Details)
Publisher : Cambridge University Press; 1st edition (July 17, 2014)
Language : English
Hardcover : 414 pages
ISBN-10 : 1107057132
ISBN-13 : 978-1107057135
Item Weight : 2 pounds
Dimensions : 7 x 1.13 x 10 inches
Customers say
Customers find the book’s introduction excellent for beginners. They say it contains good introductory insights and fundamental principles. However, opinions are mixed on readability, with some finding it well-written and concise, while others say it’s difficult to read the math symbols on the kindle.
AI-generated from the text of customer reviews
Machine learning is a branch of artificial intelligence that enables computers to learn and improve from experience without being explicitly programmed. It involves developing algorithms and statistical models that allow computers to perform specific tasks by analyzing and interpreting large amounts of data.
There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model on labeled data, where the desired output is known. Unsupervised learning involves training a model on unlabeled data, where the model must find patterns and relationships on its own. Reinforcement learning involves training a model to make decisions based on feedback from its environment.
Machine learning is used in a wide range of applications, such as image and speech recognition, natural language processing, recommendation systems, and autonomous vehicles. It has the potential to revolutionize industries and improve efficiency and accuracy in various tasks.
Understanding machine learning requires knowledge of statistics, linear algebra, and programming languages such as Python and R. It also requires a solid understanding of algorithms and data structures.
Overall, machine learning is a powerful tool that has the potential to transform the way we live and work. By understanding the core concepts and principles of machine learning, we can harness its capabilities and leverage its potential for innovation and progress.
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