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Machine learning and deep learning using Python and Tensorflow Book / Venkat Reddy Konasani, Shailendra Kadre.

By: Contributor(s): Material type: TextTextDescription: xix, 533 pages : illustrations ; 27 cmISBN:
  • 9781260462296 (hardback)
  • 1260462293
Subject(s): DDC classification:
  • 006.31 23
Other classification:
  • 006.31
Summary: "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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Junaid Zaidi Library, COMSATS University Islamabad 006.31 KON-M 62581 (Browse shelf(Opens below)) Checked out 09/02/2024 10001000062581
Total holds: 0

Includes index

"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.

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