3 ms·
As someone who self-taught essentially this over the past couple years, I'm not sure what benefit it would bring. Both developing and deploying models are alrea
by mxkopy 3y ago
As someone who self-taught essentially this over the past couple years, I'm not sure what benefit it would bring. Both developing and deploying models are already domains well established enough to not be covered by a couple courses (I'll be honest it doesn't seem like the material is 9 courses worth). You can hire an 'AI Engineer' or freely use an open source SOTA model developed by a team of PhDs.
- uxcolumbo 3y agoWhat’s your suggested path for someone new to this to learn about ML and how it can solve business problems? Deeplearning.ai Fast.ai Kaggle.com ?
- deleted 3y ago[deleted]
- mxkopy 3y agoI'm not Google weirdo
- uxcolumbo 3y agoI was basically asking what was your path to self learn ML. But thanks for your very insightful answer.
- mxkopy 3y agoSQL and XGBoost will solve 95% of your business problems. It's boring but it's true. If you're trying to create the Terminator for real, that's when you start looking at the JAX/TensorFlow/PyTorch docs. I started with that first, and paid attention to the math along the way. If you go math-first you can quickly lose the forest for the trees. But you can find pretty in-depth tutorials and source code for any of those frameworks (and the math) on Google.
- __rito__ 3y agoI studied Physics in college, so I mostly knew the Math. Here's what I used to self-learn: 1. Machine Learning for Absolute Beginners by Oliver Theobald 2. ISLR 3. Machine Learning by Andrew Ng on Coursera 4. Deep Learning by Andrew Ng on Coursera 5. fast.ai 6. Sebastian Raschka's PyTorch book Good Math refreshers: 1. Mathematics for Machine Learning Specialization by Imperial College London 2. Linear Algebra and Calculus series by 3blue1brown on YT Later I delved deep into Computer Vision for profession, and Edge AI for personal projects.