I’m switching from Blockchain development to Machine Learning. After working deeply in blockchain, I’ve decided to specialize in ML instead. Not because blockchain is “dead” — but because ML in 2025 has more depth, demand, and long-term leverage. For the next 60 days, I’ll follow a strict plan using only free resources: Foundations Auditing the PyTorch for Deep Learning Professional Certificate on DeepLearning.AI. (No certificate. Just skills.) Real projects Competing on Kaggle to build models that actually solve problems. Rank doesn’t matter. Execution does. Public proof Publishing every project on GitHub with clear READMEs: problem, approach, results. Deployment Turning models into simple apps or APIs so others can use them. I’ll share progress, mistakes, and results along the way. If you’ve transitioned between specializations, what was the hardest part? [image]

[image] Guide for Machine Learning, NLP, Computer Vision - (Roadmap) Feedback AI Discussions Hello everyone, Hello everyone, I hope you’re all doing great! I’ve been working on an academic project for UX design, and as part of it, I had to create a new feature for any website. I thought DeepLearning.AI was a great place to apply my skills and knowledge. I started by focusing on a common problem in the community: “Where should I start? Is there any roadmap for learning AI?” This is a question I’ve seen many people post here on the forum. So, I did some research and analyzed different…

[image] Alisci: Auditing the PyTorch for Deep Learning Professional Certificate on DeepLearning.AI. (No certificate. Just skills.) Auditing a course does not give you the same learning experience as enrolling in the course and completing the graded assignments.

Hello, I used to work in blockchain and now I am migrating to Ml

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balaji.ambresh December 21, 2025, 10:40am 2

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Hello, I used to work in blockchain and now I am migrating to Ml

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