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About the Author Tom Hope is an applied machine learning researcher and data scientist with extensive background in academia and industry.He has background as a senior data scientist in large international corporation settings, leading data science and deep learning R&D across multiple domains including web mining, text analytics, computer vision,sales and marketing, IoT, financial forecasting and large-scale manufacturing. Previously he was at a successful e-commerce startup in its early days, leading data science R&D. He has also served as a data science consultant for major international companies and startups. His research in computer science, data mining and statistics revolves around machine learning, deep learning, NLP, weak supervision and time-series.Hezi Reshef is an applied researcher and PhD student in Machine Learning at the Hebrew University, developing Machine Learning and Deep Learning methods for wearable device data, and working on using wearable devices to monitor patient health. He has worked at Intel Corp., leading Deep Learning R&D for monitoring and predicting patient outcomes using remote sensing and wearables. Prior to Intel, Hezi was at Microsoft, leading Machine Learning R&D for mining telemetry data, predicting software bugs, user segmentation, and other projects.Itay Lieder is an applied researcher in Machine Learning and Computational Neuroscience and a PhD student at the Hebrew University, in collaboration with the Gatsby Computational Neuroscience Unit at UCL, studying the human perception with massive crowd-sourcing experiments on Amazon Turk. His current work focuses on predicting and understanding the way humans react to sounds (e.g. music), via multiple online interactive experiments. He has worked for large international corporations, leading Deep Learning R&D in text analytics and web mining for sales and marketing. Read more Click Here to Read Learning TensorFlow: A Guide to Building Deep Learning Systems Online! Hi there My name is Michele Harper and I am here to tell you my feelings on this great book written Learning TensorFlow: A Guide to Building Deep Learning Systems recognized as Learning TensorFlow: A Guide to Building Deep Learning Systems. With a lot of phony Learning TensorFlow: A Guide to Building Deep Learning Systems reviews published on the internet lots of readers find it hard finding dependable info

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Books Tagged: WildML Artificial Intelligence, Deep Learning, and NLP Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. Python Machine Learning - Second Edition | PACKT Books Deep learning systems continue to gain widespread adoption in the enterprise, tackling photo and voice recognition, customer service interactions, and even spotting ... Deep Learning AMI Amazon Web Services Struggling to get started with deep learning for computer vision? My new book will teach you all you need to know. IBM Research Distributed Deep Learning code breaks ... You want a cheap high performance GPU for deep learning? In this blog post I will guide through the choices, so you can find the GPU which is best for you. Advanced AI: Deep Reinforcement Learning in Python | Udemy Apache MXNet is a fast and scalable training and inference framework with an easy-to-use, concise API for machine learning. MXNet includes the Gluon interface that ... Which GPU(s) to Get for Deep Learning - Tim Dettmers TensorFlow was originally a deep learning research project of the Google Brain Team that has since becomeby way of collaboration with 50 teams at Googlea new ...

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