Python machine learning : machine learning and deep learning with python, scikit-learn, and tensorflow 2 (Record no. 44887)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02050nam a22001937a 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781789955750 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.133 |
| Item number | RAS |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Raschka, Sebastian |
| 245 ## - TITLE STATEMENT | |
| Title | Python machine learning : machine learning and deep learning with python, scikit-learn, and tensorflow 2 |
| 250 ## - EDITION STATEMENT | |
| Edition statement | Third edition |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Birmingham : |
| Name of publisher | Packt Publishing, Limited, |
| Year of publication | [2019] ©2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xxi, 741 pages : |
| Other physical details | illustrations |
| 500 ## - GENERAL NOTE | |
| General note | Includes index<br/>"Third edition includes TensorFlow 2, GANS, and reinforcement learning" |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Giving computers the ability to learn from data --<br/>Training simple machine learning algorithms for classification --<br/>A tour of machine learning classifiers using scikit-learn --<br/>Building good training sets-data preprocessing --<br/>Compressing data via dimensionality reduction --<br/>Learning best practices for model evaluation and hyperparmeter tuning --<br/>Combining different models for ensemble learning --<br/>Applying machine learning to sentiment analysis --<br/>Embedding a machine learning model into a web application --<br/>Predicting continuous target variables with regression analysis --<br/>Working with unlabeled data-clustering analysis --<br/>Implementing a multilayer artificial neural network from Scratch --<br/>Parallelizing neural network training with TensorFlow --<br/>Going deeper --<br/>The mechanics of TensorFlow --<br/>Classifying images with deep convolutional neural networks --<br/>Modeling sequential data using recurrent neural networks --<br/>Generative adversarial networks for synthesizing new data --<br/>Reinforcement learning for decision making in complex environments |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for TensorFlow 2 and the latest additions to ... |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Python. |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Mirjalili, Vahid |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Reference Books |
| Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|---|---|---|---|
| Reference | Main Library | Main Library | Reference | 08/11/2021 | Purchase | 11225.00 | 005.133 RAS | 016122 | Reference Books |