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Buy Hands-On Artificial Intelligence for IoT by Kapoor, Amita online on desertcart.ae at best prices. ✓ Fast and free shipping ✓ free returns ✓ cash on delivery available on eligible purchase. Review: très complet! Review: This book was inspired by my work at Oxford University I have known Amita from her previous book (co-authored with Antonio Gulli) but I have not contributed to this book Based on my experience in teaching AI for IoT, it is not an easy subject due to its vast scope. This book first covers the Principles and then lays the groundwork in terms of tools(ex keras), datasets(ex air quality) and File formats (ex JSON) The book then cover Machine Learning in depth(linear regression, Logistic regression, SVMs, Naive Bayes, Decision trees, Ensemble learning ) followed by Deep Learning(Multi layer perceptron, CNN, RNN, Autoencoders) and then covers more complex algorithms(Genetic Algorithms, Reinforcement Learning and GANs). This is followed by Distributed AI(Spark) followed by application areas (Smart homes, Smart cities and Industrial IoT) The book then combines these ideas together in the last section Overall, it is a comprehensive and a hand-on approach What could be improved? More coverage on the Cloud and the Edge technologies What’s the best feature? The hands-on (coding based) approach Overall, its very much recommended
| Customer reviews | 4.2 4.2 out of 5 stars (15) |
| Dimensions | 19.05 x 2.24 x 23.5 cm |
| Edition | Standard Edition |
| ISBN-10 | 1788836065 |
| ISBN-13 | 978-1788836067 |
| Item weight | 667 g |
| Language | English |
| Print length | 390 pages |
| Publication date | 31 January 2019 |
| Publisher | Packt Publishing |
C**N
très complet!
A**R
This book was inspired by my work at Oxford University I have known Amita from her previous book (co-authored with Antonio Gulli) but I have not contributed to this book Based on my experience in teaching AI for IoT, it is not an easy subject due to its vast scope. This book first covers the Principles and then lays the groundwork in terms of tools(ex keras), datasets(ex air quality) and File formats (ex JSON) The book then cover Machine Learning in depth(linear regression, Logistic regression, SVMs, Naive Bayes, Decision trees, Ensemble learning ) followed by Deep Learning(Multi layer perceptron, CNN, RNN, Autoencoders) and then covers more complex algorithms(Genetic Algorithms, Reinforcement Learning and GANs). This is followed by Distributed AI(Spark) followed by application areas (Smart homes, Smart cities and Industrial IoT) The book then combines these ideas together in the last section Overall, it is a comprehensive and a hand-on approach What could be improved? More coverage on the Cloud and the Edge technologies What’s the best feature? The hands-on (coding based) approach Overall, its very much recommended
R**A
The book covers wide spectrum of AI topics from machine learning to deep learning, genetics algorithm, reinforcement learning, H2O etc to build smart AI models. Overall recommending and must read book.
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