Optimizing Machine Learning with TensorFlow, ActivePython and Intel

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

In this webinar co-hosted by Intel, you will get a general introduction to working with Tensorflow and its surrounding ecosystem, general problem classes, where you can get big acceleration, and why run 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

Download the slides (PDF) here.

Speakers:
Mohammad Ashraf Bhuiyan, Intel Artificial Intelligence Group, Senior Software Engineer
Pete Garcin, Developer Advocate, ActiveState