Machine Learning and Deep Learning Using Python and TensorFlow
Seiten
2021
McGraw-Hill Education (Verlag)
978-1-260-46229-6 (ISBN)
McGraw-Hill Education (Verlag)
978-1-260-46229-6 (ISBN)
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
Understand the principles and practices of machine learning and deep learning
This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text.
Coverage includes:
Machine learning and deep learning concepts
Python programming and statistics fundamentals
Regression and logistic regression
Decision trees
Model selection and cross-validation
Cluster analysis
Random forests and boosting
Artificial neural networks
TensorFlow and Keras
Deep learning hyperparameters
Convolutional neural networks
Recurrent neural networks and long short-term memory
Understand the principles and practices of machine learning and deep learning
This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text.
Coverage includes:
Machine learning and deep learning concepts
Python programming and statistics fundamentals
Regression and logistic regression
Decision trees
Model selection and cross-validation
Cluster analysis
Random forests and boosting
Artificial neural networks
TensorFlow and Keras
Deep learning hyperparameters
Convolutional neural networks
Recurrent neural networks and long short-term memory
| Erscheinungsdatum | 24.02.2021 |
|---|---|
| Zusatzinfo | 50 Illustrations |
| Verlagsort | OH |
| Sprache | englisch |
| Maße | 221 x 277 mm |
| Gewicht | 1347 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-260-46229-3 / 1260462293 |
| ISBN-13 | 978-1-260-46229-6 / 9781260462296 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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