Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots


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Fundamentals of Data Science Data Mining Machine Learning Deep Learning and IoTs


Fundamentals of Data Science Data Mining Machine Learning Deep Learning and IoTs

Author: Dr. A. SIVAKUMAR

language: en

Publisher: SK Research Group of Companies

Release Date: 2021-12-27


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Dr. A. SIVAKUMAR, Assistant Professor, Department of Computer Science, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu. SULAIMAN AL MASWARI, SOLAF MOHAMAD, GOURAV SONONE, Department of Information Technology, Rathinam College of Arts and Science, Coimbatore, Tamil Nadu.

Fundamentals of Data Science DataMining MachineLearning DeepLearning and IoTs


Fundamentals of Data Science DataMining MachineLearning DeepLearning and IoTs

Author: Dr. P. Kavitha

language: en

Publisher: Leilani Katie Publication

Release Date: 2023-12-23


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Dr. P. Kavitha, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India. Mr. P. Jayasheelan, Assistant Professor, Department of Computer Science, Sri Krishna Aditya College of arts and Science, Coimbatore, Tamil Nadu, India. Ms. C. Karpagam, Assistant Professor, Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India. Dr. K. Prabavathy, Assistant Professor, Department of Data Science and Analytics, Sree Saraswathi Thyagaraja College, Pollachi, Coimbatore, Tamil Nadu, India.

Deep Learning for Coders with fastai and PyTorch


Deep Learning for Coders with fastai and PyTorch

Author: Jeremy Howard

language: en

Publisher: O'Reilly Media

Release Date: 2020-06-29


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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala