Tag Archives: machine learning

A New Specialty Certification is on the Way from AWS…

Machine Learning

And it should come as no big surprise!

AWS Certified Machine Learning – Specialty

This certification exam is currently in Beta as I write this. Yes – I plan on going and taking a look and will report back.

The AWS Certified Machine Learning – Specialty beta examination is intended for individuals with one to two years of hands-on experience developing, architecting, or running machine learning (ML)/deep learning workloads on the AWS Cloud.

It validates an examinee’s ability to:

  • Select and justify the appropriate ML approach for a given business problem.
  • Identify appropriate AWS services to implement ML solutions.
  • Design and implement scalable, cost-optimized, reliable, and secure ML solutions.

Recommended AWS and General IT Knowledge and Experience:

  • The ability to express the intuition behind basic ML algorithms
  • Experience performing basic hyperparameter optimization
  • Experience with ML and deep learning frameworks
  • The ability to follow model-training best practices
  • The ability to follow deployment and operational best practices

If you are really interested in this cert – be sure to download the exam guide:

https://d1.awsstatic.com/training-and-certification/machinelearning/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide_v1.1_FINAL.pdf

AWS Computing at Scale and Machine Learning

Machine Learning

Here is the continuation of my notes from the Keynote addresses at the 2017 AWS Re: Invent conference. Enjoy!

Computing at Scale

  • Growth in EC2 has been HUGE when you look at the increase in cores running in AWS
  • But GPU and FPGA core growth rates have crushed that! It has been exponential growth

Machine Learning

  • Machine Learning always seems to come up about every 5 years – then fades away again
  • This time it is “sticking” thanks in large part to the scale that the cloud offers
  • Examples:
    • Tu Simple with autonomous transport (trucking industry)
    • Matrix Analytics with tumor recognition for cancer screening
    • Clemson University and natural language learning – in the span of two hours, they had 1.1 million cores running on AWS!
  • There are three big drivers of the explosion in this technology:
    • HW acceleration capabilities thanks to technology from the likes of Nvidia (P3.16XLARGE instances)
    • Improvements in the Machine Learning frameworks
    • A rapidly growing community
      • GLUON
      • ONNX
      • NNVM and TVM