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It's totally possible. Which isn't to say that it's easy. If you go down that road, be prepared to sacrifice your social life for several years. The most frust

It's totally possible. Which isn't to say that it's easy. If you go down that road, be prepared to sacrifice your social life for several years. The most frustrating thing will be going through basics that don't seem connected to your eventual goal of ML; this is potentially a long phase. I'd recommend Khan Academy for the math basics. Schaum's Outlines series for lots of worked problems. I'd recommend Strang's MIT OCW videos and books for Linear Algebra. I first learned calculus from an economics book, probably best not repeated ;). Bishop's PRML book is a good source on probability, Bayesian stats and machine learning. I did a part time MSc in applied stats while working full time. Even in the MOOC era, there's nothing like real exams to focus your efforts.

RandomInteger4 10y ago
Khan Academy is a great place to start. I second that recommendation. Although I was pretty confident in my maths up through basic calculus, I began fresh earlier this year starting from pre-algebra on their videos and problem sets. I took the approach of looking at the mind as a muscle and if I had taken a long break from lifting, I wouldn't jump right back in lifting the same weights. The analogy isn't perfect, but I feel like it helped to reinforce the old basic neural pathways in order to prime my mind for more difficult topics. EDIT: Also the achievement points aspect helped as a learning tool as well.