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Machine Learning with TensorFlow


In this on-demand webinar, you’ll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.



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Tensorflow, developed by Google, has become the most popular framework for deep learning, and now operates on a variety of devices including multicore CPUs, general purpose GPUs, mobile devices, and custom ASICs.

In this on-demand webinar hosted by Intel and ActiveState, you’ll get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why you should be running on a CPU.

Topics covered:

  • Ideal use cases for TensorFlow on CPUs, including which models and types of operations benefit the most
  • Proposed benchmarks, projected accelerations, and how to tune performance for your systems
  • Advanced topics like using multiple nodes to train on large data sets<
  • How Intel has optimized TensorFlow for Intel CPUs by fully utilizing multi-core processors, AVX instructions, and high performance memory systems
  • How other Intel MKL-optimized data science packages included with ActivePython can help accelerate your algorithms

Speakers:

Mohammad Ashraf Bhuiyan, Intel Artificial Intelligence Group, Senior Software Engineer

Pete Garcin, Developer Advocate, ActiveState


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