000			03296cam a2200301zu 4500
001			88900550
003			FRCYB88900550
005			20250107233359.0
006			m o d
007			cr un
008			250108s2020 fr | o|||||0|0|||eng d
020			_a9781839219856
035			_aFRCYB88900550
040			_aFR-PaCSA _ben _c _erda
100	1		_aBaig, Mirza Rahim
245	0	1	_aThe Deep Learning Workshop _c['Baig, Mirza Rahim', 'Joseph, Thomas V.', 'Sadvilkar, Nipun']
264		1	_bPackt Publishing _c2020
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aBaig, Mirza Rahim
700	0		_aJoseph, Thomas V.
700	0		_aSadvilkar, Nipun
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88900550 _qtext/html _a
520			_aTake a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Key Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition Study the architecture of different neural networks Book Description Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You'll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you'll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you'll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you'll have learned the skills essential for building deep learning models with TensorFlow and Keras. What you will learn Understand how deep learning, machine learning, and artificial intelligence are different Develop multilayer deep neural networks with TensorFlow Implement deep neural networks for multiclass classification using Keras Train CNN models for image recognition Handle sequence data and use it in conjunction with RNNs Build a GAN to generate high-quality synthesized images Who this book is for If you are interested in machine learning and want to create and train deep learning models using TensorFlow and Keras, this workshop is for you. A solid understanding of Python and its packages, along with basic machine learning concepts, will help you to learn the topics quickly.
999			_c73180 _d73180