Hey everyone, ​I’m looking to seriously level up my practical ML skills, and literally every roadmap, thread, and YouTube video points to Aurélien Géron’s Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (and the newer PyTorch-focused adaptations/community versions). ​Before I drop the cash and commit a few months of my life to grinding through it, I wanted to get an honest vibe check from people who have actually built things with it: ​Theory vs. Practice: Is it actually "hands-on," or am I going to get bogged down in dense mathematical proofs by chapter 3? ​Relevance: How well does the Scikit-Learn to PyTorch pipeline translate to real-world, industry production right now? ​The Grind: For those who finished it (or got halfway), what’s the best way to tackle it? Did you build side projects alongside it, or just stick to the book's notebooks? ​Would love to hear your honest reviews, triumphs, or even warnings.…