cuDF, cuML & RAPIDS: GPU Accelerated Data Science with Paul Mahler
Today we’re joined by Paul Mahler, senior data scientist and technical product manager for machine learning at NVIDIA.
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On Saturday, February 2nd we’re launching our 3rd cohort of deep learning learners through the Fast.ai Practical Deep Learning for Coders Part 1 course. This study group will meet weekly on Saturdays at 9 am Pacific Time for seven weeks, each week covering a new lesson from the course. We love this course for its ability to have participants building world-class deep learning models right out of the gate, without getting bogged down in theory.
This week’s shows are drawn from some of the great conversations I had at the recent NVIDIA GPU Technology Conference, and they’re brought to you by Dell. If you caught my tweets from GTC, you may already know that one of the announcements this year was a new reference architecture for Data Science Workstations, powered […]
Bits & Bytes AWS offers Nvidia’s Tesla T4 chip for AI inference. The new EC2 instances, with Tesla T4 GPUs, will provide AWS customers with a new option for reduced-cost AI inference. T4 will also be available through the Amazon Elastic Container service for Kubernetes. Qualcomm launches new, AI-enabled smart speaker platform.The new Qualcomm QCS400 SoC series brings its […]
A few weeks ago I had a chance to attend the TensorFlow Developer Summit on the Google Cloud campus in Sunnyvale, California. I had a great time at the Summit, meeting a bunch of TWiML Talk listeners and friends of the show, and learning about all the new features released as part of the new […]
Bits & Bytes Google announces TensorFlow 2.0 Alpha, TensorFlow Federated, TensorFlow Privacy. At the 3rd annual TensorFlow Developer Summit, Google announced the first alpha release of TensorFlow 2.0 and several other new releases such as: TensorFlow Federated – a new open-source framework that allows developers to use all the ML-training features from TF while keeping the data local; TensorFlow […]