These creators make AI/ML truly understandable the real heroes for anyone learning this field🤩
Vaishnavi
10.1K posts
- Machine learning is 90% cleaning data, 9% waiting for training, and 1% praying it works.😁
- After analyzing the job market, I realized one important thing no matter which domain you choose, whether it’s DevOps, Web Development, AI/ML, or Cloud, you’re bound to face rejections. So don’t think you’ve chosen the wrong path. Stay consistent, keep learning, & keep pushing
- According to you, what’s the maximum time needed to fully learn AI & ML.? 🤔
- Today marks the beginning of my ML learning journey! Here are my notes from Day 1 — drop your thoughts in the comments below!
- Am I the only one here who genuinely loves the math behind the entire ML process?
- Harvard has released its ML course (CS 249) as a free, interactive textbook covering system design, data engineering, deployment, MLOps, and edge AI. It’s a great resource for anyone looking to understand how real-world ML systems are built and run🤩
- Best Github Respositories for AI Engineer Beginner Level – Build Your AI Foundation 1. AI for Beginners (Microsoft) A complete 12-week curriculum covering AI fundamentals — from classical AI to ethics. 🔗 lnkd.in/ehVdWc5U
- Day 3: Today I learned about the importance of data in machine learning how the quality, quantity, and type of data play a key role in building effective ML models.
