Welcome to Gratitude Driven, a weekly newsletter where I share practical ideas and insights across personal growth, professional development, and the world of AI and data science.
In This Newsletter
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This New Year, Don’t Overthink Agentic AI
Kick off 2026 with this FREE webinar and start building Agentic AI for real.
Interview Kickstart’s 14-week Agentic AI program is for engineers, PMs, and tech leaders who want to learn by building, not by watching slides. You’ll complete two practical projects to confidently add to your resume.
The program adapts to your role. Engineers work with Python-based tools, while PMs and leaders use no-code and low-code platforms. If a job switch is on your mind, you can also add FAANG-style interview prep.
I’ve mentored with Interview Kickstart and seen firsthand how seriously they take practical skills and outcomes. You’ll learn from ex-FAANG+ experts building AI systems every day.
Over 25,000 people have leveled up their careers—and in 2026, you could be one of them. Check out the webinar here!
This Is The Best ML Portfolio Project I’ve Ever Seen
If you’ve ever brainstormed ML portfolio project ideas, I bet you didn’t think about having a fish trade stocks. But maybe you should have.
This video is great. The TL;DR is that he builds a system that monitors his fish’s movement in the tank (computer vision), executes trades using an API based on where the fish spends more time, builds a custom dataset creation pipeline to analyze the sentiment of posts on r/wallstreetbets, builds a sentiment classifier, and then a bot runs daily to scrape top posts, run sentiment analysis, and buy stocks from positive posts.
Ultimately, the fish outperforms r/wallstreetbets.
Here's why this works as a project:
It’s completely unique from beginning to end. There is no way to follow a tutorial here — Michael had to come up with the idea, figure out all the components, and do the entire thing independently.
It demonstrates multiple skills. Computer vision, custom data labeling, web scraping, using APIs, sentiment analysis + model training, and deployment. (This could also use more rigorous evaluation and monitoring, but it's a YouTube video not a prod system so he gets a pass.)
Shows engineering judgment. The fish tracking uses a deliberately simple approach (just a white background + orange pixel filter instead of over-engineering with YOLO or something fancy). Knowing when the simple solution is the right solution is a skill in and of itself.
Clever problem diagnosis. He recognized that off-the-shelf sentiment models would fail on WSB's weird vocabulary and built a custom dataset to fix it.
It's a deployed system. This ran for months with actual money, not a Jupyter notebook that just lives in a GitHub repo forever. (Obviously I’m not saying you need $50k for a project. This would have been just as cool with $5 on meme coins or something).
Making a video is an amazing way to showcase the work.
It's funny. I would for sure want to interview this guy once I saw the combination of skills, intelligence, and sense of humor.
Honestly, lots of Michael Reeves’ videos showcase super clever ideas for ML projects (robotics aside). This all goes to show how important and impactful it can be to think outside of the box. You don't need to (and in fact, you shouldn’t) limit yourself to well-defined problem spaces. Get creative and have fun with it!
Are AI/ML Certificates Worth It?
In my coaching work, I’m often asked whether it makes sense to get a certificate. The answer isn’t just yes or no — it really depends on your situation. This video breaks down the decision framework that I use, and also shares the best certificates to get if it makes sense for your situation.
Blog version is here, as usual.
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