O'Reilly TensorFlow World 2019 - Santa Clara, CA Free Download

O’Reilly TensorFlow World 2019 – Santa Clara, CA
English | Size: 58.24 GB + 60.81 GB
Genre: eLearning

Open source TensorFlow 2.0 is driving the machine learning (ML) revolution around the globe. The TensorFlow World Conference Santa Clara 2019—the first international conference devoted to TensorFlow—provided the thousands who attended the conference with an extraordinary opportunity to see TensorFlow 2.0 in action, discover new ways to use it, and learn how to successfully implement it in their own enterprises. This video compilation offers you the chance to experience the TensorFlow World Conference yourself. If you get it and explore it, you’ll come away with a firm understanding of the entire machine learning stack, TensorFlow 2.0, and the reasons why companies like Spotify, LinkedIn, Amazon, Twitter, and Uber use TensorFlow to solve complex business problems.

Highlights include:

A front row view for all of the best keynotes, tutorials, and technical sessions from the TensorFlow World Conference Santa Clara 2019.
Complete presentations from some of the world’s top TensorFlow practitioners, including talks by the people and teams who developed TensorFlow.
Keynote addresses from TensorFlow’s leaders, such as Google Brain co-founder Jeff Dean; Theodore Summe, the head of product for Cortex, Twitter’s central ML organization; and Megan Kacholia, VP of Engineering for Google Research.
Deep-dive tutorials, including Laurence Moroney’s (Google Brain) primer on ML with TensorFlow; Sandeep Gupta’s (Google) review of ML in JavaScript using TensorFlow.js; and Neelima Mukiri’s (Cisco) intro to model building and optimization for TensorFlow in any Kubernetes environment.
Applications sessions focusing on real-world TensorFlow implementations, like Asif Hasan’s (Quantiphi) talk on using ML to both predict cancer recurrence and recommend treatment; Bhushan Jagyasi’s (Accenture) survey of TensorFlow successes in banking and insurance; and Hamel Husain’s (GitHub) review of automating developer workflows on GitHub with TensorFlow.
Core Technologies sessions, where you’ll hear directly from TensorFlow team members such as Paige Bailey (Google) on TensorFlow Swift, a next-generation ML platform; Raziel Alverez (Google) on TensorFlow model optimization techniques; and Robby Neale (Google) on how to build models with tf.text.
Accelerators sessions, including Victoria Rege (Graphcore) on how to target high-performance ML accelerators using TF XLA; Sudipta Sengupta (AWS) on the basics of integrating deep learning accelerators with TensorFlow; and Manjunath Kudlur (Cerebras Systems) on the software stack that connects users and TensorFlow to the Cerebras WSE deep learning accelerator.
Production pipeline sessions, such as Robert Crowe’s (Google) tutorial on using TensorFlow TFX to create ML pipelines; Animesh Singh’s (IBM) intro to TFX, hybrid cloud ML pipelines, and Kubeflow; and Shajan Dasan’s (Twitter) explanation of how Twitter builds reliable, high-scale TensorFlow inference pipelines.
Text, Language, and Speech sessions, where you’ll learn the basics of processing human communication from experts like Kiwisoft’s Aurélien Géron (on natural language processing using transformer architectures) and NVIDIA’s Jason Li (on end-to-end speech recognition using the OpenSeq2Seq deep learning toolkit).
Mobile and Edge sessions, such as Kaz Sato (Google) on using AutoML Vision to support vision recognition model training on mobile phones and Alasdair Allan (Babilim Light Industries) on using TensorFlow Lite on small, embedded devices.
Multiple sessions on TensorFlow in the enterprise; TensorFlow ethics, and security; and on TensorFlow in ML research.

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