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Introducing Machine Learning (Developer Reference)
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Introducing Machine Learning delivers practical knowledge to make the most of immense opportunities.
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- Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning.· 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you· Explore what’s known about how humans learn and how intelligent software is built· Discover which problems machine learning can address· Understand the machine learning pipeline: the steps leading to a deliverable model· Use AutoML to automatically select the best pipeline for any problem and dataset· Master ML.NET, implement its pipeline, and apply its tasks and algorithms· Explore the mathematical foundations of machine learning· Make predictions, improve decision-making, and apply probabilistic methods· Group data via classification and clustering· Learn the fundamentals of deep learning, including neural network design· Leverage AI cloud services to build better real-world solutions fasterAbout This Book· For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills· Includes examples of machine learning coding scenarios built using the ML.NET library
| Publisher | Microsoft Press |
| Publication date | 20 Feb. 2020 |
| Edition | 1st |
| Language | English |
| Print length | 400 pages |
| ISBN-10 | 0135565669 |
| ISBN-13 | 978-0135565667 |
| Item weight | 1.05 kg |
| Dimensions | 18.75 x 2.31 x 23.19 cm |
| Part of series | Developer Reference |
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Features & Benefits
- Learn core machine learning concepts to solve real-world problems.
- Understand the ML.NET library for data processing and evaluation.
- Explore deep learning techniques including neural networks.
- Master a complete machine learning pipeline from problem identification to model delivery.
- Utilize AutoML to optimize the pipeline for various datasets.
- Gain insights into AI cloud services for efficient solution development.
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