CSU-Carig
Machine learning and deep learning using Python and Tensorflow / Venkat Reddy Konasani, Shailendra Kadre.
by Konasani, Venkat Reddy,
| Item type | Location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Books
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General Collection | General Works | 006.31 K821 2021 (Browse shelf) | Available | 009909 |
Browsing Cagayan State University - Carig Library Shelves , Shelving location: General Collection , Collection code: General Works Close shelf browser
| 006.3 M9848 2015 Introduction to data mining and soft computing techniques / | 006.3 M9848 2015 Introduction to data mining and soft computing techniques / | 006.31 D4575 2022 Design of intelligent application using machine learning and deep learning techniques / edited by Ramchandra S. Mangrulkar [and four others]. | 006.31 K821 2021 Machine learning and deep learning using Python and Tensorflow / Venkat Reddy Konasani, Shailendra Kadre. | 006.31 M1497 2022 Machine learning and deep learning techniques in wireless and mobile networking systems / edited by K. Suganthi [and three others]. | 006.312 Z17 2014 (Not for Overnight) Social media mining : an introduction / | 006.37 Sh5296 2001 Computer vision / Linda G. Shapiro, George C. Stockman. |
Includes bibliographical references and index.
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.
"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."--
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