"TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits--simplicity, efficiency, and flexibility--of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advance projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem."--Publisher's description.

�ber die Autorinnen und Autoren

Ankit Jain currently works as a senior research scientist at Uber AI Labs, the machine learning research arm of Uber. His work primarily involves the application of deep learning methods to a variety of Uber's problems, ranging from forecasting and food delivery to self-driving cars. Previously, he has worked in a variety of data science roles at the Bank of America, Facebook, and other start-ups. He has been a featured speaker at many of the top AI conferences and universities, including UC Berkeley, O'Reilly AI conference, and others. He has a keen interest in teaching and has mentored over 500 students in AI through various start-ups and bootcamps. He completed his MS at UC Berkeley and his BS at IIT Bombay (India).

Armando Fandango creates AI empowered products by leveraging his expertise in deep learning, machine learning, distributed computing, and computational methods and has provided thought leadership roles as Chief Data Scientist and Director at startups and large enterprises. He has been advising high-tech AI-based startups. Armando has authored books titled Python Data Analysis - Second Edition and Mastering TensorFlow. He has also published research in international journals and conferences.

Amita Kapoor is an Associate Professor at the Department of Electronics, SRCASW, University of Delhi. She has been teaching neural networks for twenty years. During her PhD, she was awarded the prestigious DAAD fellowship, which enabled her to pursue part of her research work at the Karlsruhe Institute of Technology, Germany. She was awarded the Best Presentation Award at the International Conference on Photonics 2008. Being a member of the ACM, IEEE, INNS, and ISBS, she has published more than 40 papers in international journals and conferences. Her research areas include machine learning, AI, neural networks, robotics, and Buddhism and ethics in AI. She has co-authored the book, Tensorflow 1.x Deep Learning Cookbook, by Packt Publishing.

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

GreatBookPrices.com is your top source for finding new books at the absolute lowest prices, guaranteed ! We offer big discounts - everyday - on millions of titles in virtually any category, from Architecture to Zoology -- and everything in between. Discover great deals and super-savings, on professional books, text book titles, the newest computer guides, or your favorite fiction authors. You'll find it all - at HUGE SAVINGS - at GreatBookPrices. Browse through our complete online product catalog today. Serving customers around the world for years, we help thousands find just the books they're looking for -- at incredibly low, bargain prices.

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

Far Corner Europe Limited
19-20 Bourne Court, 19-20 Bourne Court, Woodford Green, IG8 8HD, United Kingdom

Gesch�ftsbedingungen und Versandinformationen

Verkaufsbedingungen

Company Name: GreatBookPricesUK
Legal Entity: Far Corner Europe Limited
Address: 19-20 Bourne Court, Southend Road, Woodford Green Essex, UK IG8 8HD
Registration #: 10691061
Authorized representative: Danielle Hainsey

Versandbedingungen

Our warehouses across the globe are fully operational without substantial delays. We are working hard and continue to overcome the daily challenges presented by COVID-19. There have been reports that delivery carriers are experiencing large delays resulting in longer than normal deliveries to customers. We would like to apologize in advance if your item arrives later than the expected delivery due date

Internal processing of your order will take about 1-2 business days. Please allow an additional 10-20 business days for Royal Mail delivery.

Impressum & Info zum Verk�ufer