My Experience at the AWS Developer Summit and Machine Learning (ML) track, 2019
Amazon Web Services had organized its 1st Developer Summit in Seattle. Approximately 65 Developers spread over various tracks ( Containers, Serverless, Databases, AI/ML, and Dev Tools) were invited from all over the globe in which I was the only one from India. The event was for 3 days in which the 1st Day was common for all the tracks and Day 2 and Day 3 focused on respectively specific tracks (in my case “AI/ML track”).
Day 1:
Amazon Web Services experts developed and tracks on the vision and strategic investments for categories like serverless, databases, and machine learning (ML)… I’m excited to start using them.
Participants got to interact with Amazon Employees and could share their current problems and feedback with any services that they use while solving real-life problems.
After the sessions, we were invited to the “Amazon Spheres” for drinks and dinner. The place was just majestic.
Day 2:
The next day started with everyone’s face lit up and recovered from Jet Lag. We all were very excited to get started with the AI/ML tracks. Excitement skyrocketed when we got an “ AWS DeepLens” from Amazon.
- AWS Deepracer workshop: AWS Deepracer is an amazon service and is the easiest way to get started with Reinforcement Learning. I was a 90 minutes session by Scott Pletcher which explained a lot about how to get started using AWS Deepracer. We also had a virtual competition of completing 100% track in the most possible time. It was tougher to make the deepracer car run slowly. Among all, I got the slowest lap time.
2. AWS Deepracer Community: Lyndon Leggate explained how to he started the AWS Deepracer Community. He was at the London AWS Summit competing in the AWS Deepracer League. There he started talking with few of the folks who were also there for the League and after the event, all of them wanted to continue the talk. So he ended up creating a slack channel for it. Since then in the last 4 months, the community has grown to more than 10,000 Deepracing Enthusiasts. He also shared the vision for this community. To join the community visit www.deepracing.io
3. Recommendation using Amazon SageMaker: Pavlos Mitsoulis, A Data Scientist at Expedia Group explained how he had built a “Hotel Recommendation System” using Amazon SageMaker. He explained how he had built the algorithm and how easy it was to train and deploy a model using Amazon SageMaker.
4. AWS DeepLens: Alex Schultz explained how he found a solution to read storybooks to his kids using AWS DeepLens. He built a solution that was trained on a lot of kid storybooks called “ReadToMe”. Using ReadToMe if a storybook is held in front of the AWS Deeplens it would read the story like a normal human being.
After this, we had a few lighting talks each for 15 minutes.
- The first one was by Or Hiltch which explained the importance of having a structured way of writing a technical blog. A blog can be structured as:
What — Explain the reader about the problem that you are going to solve.
Why — Why the reader should read the blog and what will he learn.
How — Explain how are you solving the problem
Summary — It’s very important to summarize your blog, as it makes the reader recall whatever he has read without scrolling up the blog.
2. Agustinus Nalwan explained how to keep your talk interesting to have the maximum impact of your talk. He also talked about how can we keep the audience engaged coming from different backgrounds. Be it someone who is just graduated to someone who knows everything about the topic of your talk.
3. Kesha Williams told us that she gets asked that she is always at a conference. Continuing further she explained how we can create a great social presence and to reach a point where if we enter a room, we need not have to introduce ourselves.
Kesha also shared a few tips with us:
1. Don’t be afraid to tell your story.
2. Technical expertise can’t stand on its own.
3. You don’t have to be an expert.
4. Be ready for criticism.
After all the sessions, We were taken to the Living Computer Museum. It provides a one-of-a-kind, hands-on experience with computer technology from the 1960s to the present. It honors the history of computing with the world’s largest collection of fully restored and usable supercomputers, mainframes, minicomputers, and microcomputers.
Day 3
It was the last day of our session and the morning started with everyone building up their social network with each other.
- The Technological Founder Evolution Path: The Co-founder and CTO at Skyline AI Or Hiltch explained his transformation through different phases of building up his own company. A company that started with 3 and grew to 35 demanded all kinds of different roles from him.
2. Amazon Lex: The talk on Lex by Gillian Armstrong focused not on building the bot using Lex, but on things that get neglected while building a successful Chatbot. She explained how building a chatbot from POC to Production is not a linear line but it’s an exponential curve.
3. Amazon SageMaker Ground Truth: We had a workshop by Mahendra Bairagi on Ground Truth. Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks.
4. Amazon Personalize: The Second workshop was by Chris King and yifei ma was on Amazon Personalize. It is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.
The Day and the Event concluded with Good-byes to everyone and connecting on social media for future collaborations.
Kudos to the Team (Cameron Peron, Ian Massingham, Ross Barich, and others) for organizing an impeccable event. It was a great mixture of learning, networking, and fun. Finally, Thanks to AWS for Sponsoring the complete event.
My overall experience was very good. I was very happy with how the events were scheduled and the workshops were very helpful to get us started with using the technology.
It was nice to meet amazon employees who work on the technology that we use since it helped us convey our suggestions to the respective Project Managers about the product and also give feedback on their work.
