Häftad, Engelska, 2019
Deep Learning with TensorFlow 2 and Keras
Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API
Av Antonio Gulli, Dr. Amita Kapoor, Sujit Pal
759 kr
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Beskrivning
Produktinformation
- Utgivningsdatum: 2019-12-27
- Mått: 191 x 235 x 35 mm
- Vikt: 1 187 g
- Format: Häftad
- Språk: Engelska
- Antal sidor: 646
- Upplaga: 2
- Förlag: Packt Publishing Limited
- ISBN: 9781838823412
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Mer information
Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI. Amita Kapoor, a seasoned expert in Artificial Intelligence, serves as the Chief Artificial Intelligence Officer at Retured, bringing over 25 years of experience in AI, data science, and neuroscience. Her consultancy, NePeur, stands testament to her leadership in applying AI across diverse industries, enhancing operational efficiency and business intelligence. Amita is also a devoted board member of Neuromatch Academy, where she plays a crucial role in making neuroscience and deep learning education accessible to all. Holding a PhD from the University of Delhi, she has dedicated her career to education, authoring numerous articles and papers, and creating impactful online classes. Her significant contributions extend to pioneering projects in intelligent vehicle fleet management, home surveillance through AI-powered face detection, and robust data anonymization solutions. Connect with Amita on LinkedIn. Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.
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