Blog Overview

Since I am very passionate about Machine Learning, AI, Microsoft Cognitive Toolkit (CNTK), Embedded Learning Library (ELL) and embedded edge computing IoT devices, I decided to start this blog, Everything You Always Wanted to Know About Microsoft Cognitive Toolkit But Were Afraid to Ask.

We’ll discuss broader subjects about the history, motivation, monetization of Machine Learning and AI.
I’d like to share what I learned from
Andrew Ng from Stanford,
Geoffrey Hinton from Toronto University and
Stanford CS231n: Convolutional Neural Networks for Visual Recognition
by demonstrating the deep neural network principles using Microsoft Cognitive Toolkit (CNTK).
Overarching topics

  • Machine Learning principles and put them to practice using Microsoft Cognitive Toolkit
  • What you need to be a great Machine Learning Engineer.

Here is the plan

  1. Overview
  2. Readers
  3. Layers
  4. Optimizers
  5. Workflow
  6. Train
  7. Verify
  8. Test
  9. Networks
  10. Time Machine, Sequences

I hold many certificates from Stanford and Toronto University in Machine Learning and Deep Neural Networks and many from Coursera and Udemy. I am a .NET Full Stack Software Engineer, love .NET Core, C#, Python, good food, dancing and scuba diving.

It’s gonna be fun!