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Introducing Machine Learning

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 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, 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 faster about 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 library

• Autor: Dino Esposito, Francesco Esposito
• Wydawnictwo: Pearson
• Rok wydania: 2019
• Okładka: miękka
• Liczba stron: 256
• Wymiary: 18.6 x 23 x 2 cm
• Język: angielski
• ISBN: 9780135565667