Using Intel® Distribution for Python, you can

a) achieve faster Python application performance—right out of the box—with minimal or no changes to your code
b) Accelerate NumPy*, SciPy*, and scikit-learn* with integrated Libraries such as Intel® MKL and Intel® DAAL and
c) Access the latest vectorization and multithreading instructions

The Intel® DAAL helps speed big data analytics, by providing highly optimized algorithmic building blocks for all data analysis stages. It provides a rich set of algorithms, ranging from the most basic descriptive statistics for datasets to more advanced data mining and machine learning algorithms. Intel DAAL is a highly optimized library of computationally intensive routines supporting a variety of Intel CPU architectures.

Intel® VTune™ Amplifier helps in performance analysis, by collecting key profiling data and presents it with a powerful interface that simplifies its analysis and interpretation

TensorFlow* is a leading deep learning and machine learning framework. It now integrates optimizations for Intel® Xeon® processors. This workshop provides information for developers who want to build, install, and explore TensorFlow optimized on Intel architecture.

 

What You Will Learn:

• Build and Install TensorFlow* on Intel® Architecture Neural Networks with TensorFlow
• Hands on Session on Training the model from scratch for a Sample Dataset , Intel® optimization for TensorFlow*- for Performance & Short exercise for Model optimization
• Training a Convolutional Neural Network with TensorFlow to perform image classification.
• Optimizations and performance comparisons.

STRUCTURE OF THE WORKSHOP

Theory:

• • Welcome
  • Intel® Distribution for Python
  • Parallel Python w/ Intro to MPI
  • Intel® VTune™ Amplifier for Python
  • Intel® Data Analytics Acceleration Library (Intel® DAAL)
  • Introduction to Intel Optimized Frameworks

 

Deep learning Hands-on:

• • Training the model from scratch for a Sample Dataset
  • Use transfer learning from a pre-trained Model
  • Intel® optimization for TensorFlow*- for Performance
  • Short exercise for Model optimization

Participants’ pre-requisites:

This workshop is suitable for participants with Intermediate level of Python and Linux awareness. Expected to bring their own Laptops.

Laptop: Recommended -4GB RAM with modern browser and WiFi adapter

INSTRUCTORS

Jayaraman Mahalingam (JAY)