Data vs. ML Platforms

There was an awesome thread in the Jobs channel asking if anyone has actually had any luck hiring in the community. I had heard about a few stories but one I wasn't aware of was from Nilansh Rajput getting a role at Tide.

After learning about this success story I asked Nilansh if he would be willing to share how it all transpired and what the experience was like for him.

Expecting a few short paragraphs I could add to the newsletter, the dude came back to me with a full on blog post! Pretty awesome to see the initiative and also he included some of his key takeaways for getting a job in this sector if you are just starting out in the field.

The market is hot right now! Don't leave anything on the table!

Also there have been like 5 people asking me if I know any good evangelists or Devrel people looking for a job. Reach out to me if you are interested!

To Centralize or Decentralize?

Many of you know Erik Bernhardsson from his incredible blog and his quotable tweets about data challenges and tools. Well, he joined us this week to talk about how to build data platforms, his experiences at Spotify and Better building ML systems, and where the data stack is going.

And oh by the way, we got Mike Del Balso, CEO at Tecton and former Uber machine learning lead, to join us! Mike and Erik threw around ideas they have been pondering about the space.

This was a great conversation between peers; Demetrios and I didn't even have to work that hard to ask questions, as Mike and Erik had plenty to say and learn based on each other's thoughts. Some topics we touched on were the key differences between data and ML platforms and how to walk the middle way between centralization and decentralization of platforms.

I highly recommend listening to this session for a glimpse into the perspective of two leading thinkers about machine learning and data!

Till next time,
Vishnu

This week Vishnu and I took part in an MLOps panel at the Transform X virtual conference alongside some other very predominant figures. Looks like there are a ton of great talks besides our panel that are worth checking out.

The conference doesn't cost anything either (well I mean it costs your email and some unsolicited sales emails, but those are easy enough to ignore)

On Friday, David Aponte and I will be talking at MLOps Days hosted by Glovo. You can also attend for the low cost of an email address. We plan to talk about some main pillars of MLOps and building ML empathy for SWE.

Register to join us by hitting the button below.

Cloud Tooling Deep Dive

This week's meetup is titled "Doing MLOps" for a reason. Noah Gift comes back for his second appearance to talk and 'do' with us.

We will be learning how to harness cloud technologies like AWS AppRunner to deploy and monitor machine learning models in production.

Let's be honest, getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This session takes you through what MLOps is (and how it differs from DevOps) and shows you how to operationalize your machine learning models.

Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud.

The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This session gives you a head start.

You can expect to get into this:

Learn to set up a Python project for CI/CD
Setup project scaffolding: Makefile, tests, and linting
Configure testing with Github Actions
Learn to build Microservices using Python MLOps Cookbook
Setup Python command-line tools
Setup Python Flask Microservice
Learn to deploy to AWS Cloud using AWS App runner
Setup an AWS App Runner project
Finalize a Continuous Deployment project
Verify a Machine Learning Prediction works

If you haven't heard already, we have a public cal you can subscribe to. Otherwise, see you next week by clicking on the link below.