Deep Learning Essentials
Wei Di (u. a.)
Venduto da preigu, Osnabrück, Germania
Venditore AbeBooks dal 5 agosto 2024
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Aggiungere al carrelloVenduto da preigu, Osnabrück, Germania
Venditore AbeBooks dal 5 agosto 2024
Condizione: Nuovo
Quantità: 5 disponibili
Aggiungere al carrelloDeep Learning Essentials | Wei Di (u. a.) | Taschenbuch | Englisch | 2018 | Packt Publishing | EAN 9781785880360 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Codice articolo 111327059
Get to grips with the essentials of deep learning by leveraging the power of Python
Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master.
This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network and Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, and speech recognition. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets and small datasets
By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications.
Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as TensorFlow and Keras, it would be useful to have sound programming knowledge of Python. Prior knowledge of deep learning is not required.
Wei Di is a data scientist with years of experience in machine learning and artificial intelligence. She is passionate about creating smart and scalable intelligent solutions that can impact millions of individuals and empower successful business. Currently, she works a staff data scientist in LinkedIn. She was previously associated with eBay Human Language Technology team and eBay Research Labs. Prior to that, she was with ancestry, working on large-scale data mining in the areas of record linkage. She received her PhD from Purdue University in 2011.
Anurag Bhardwaj currently leads data science efforts at Wiser Solutions, where he focuses on structuring large scale eCommerce inventory. He is particularly interested in using machine learning to solve problems on product category classification, product matching and various related problems in eCommerce. Previously, he worked on image understanding at eBay Research Labs. Anurag received his PhD and MS from the State University of New York at Buffalo and holds a BTech in computer engineering from the National Institute of Technology, Kurukshetra, India.
Jianing Wei is a senior software engineer at Google Research. He works in the area of computer vision and computational imaging. Prior to joining Google in 2013, Jianing worked at Sony US Research Center for four years in the area of 3D computer vision and image processing. Jianing obtained his Ph.D. in Electrical and Computer Engineering from Purdue University in 2010.
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