Machine learning and deep learning using Python and Tensorflow / Venkat Reddy Konasani, Shailendra Kadre.
| Author/creator | Konasani, Venkat Reddy |
| Other author | Kadre, Shailendra. |
| Format | Electronic |
| Publication Info | New York : McGraw-Hill, [2021] |
| Description | xix, 533 pages : illustrations ; 27 cm |
| Supplemental Content | Full text available from AccessEngineering |
| Subjects |
| Contents | Introduction to machine learning and deep learning -- Basics of Python programming and statistics -- 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. |
| Abstract | "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."-- Page 4 of cover. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2020949936 |
| ISBN | 9781260462296 hardcover |
| ISBN | 1260462293 hardcover |