Coming back to this, I totally get why youre stressed about the Greek symbols. I was in the same boat last year and honestly... it looks way scarier than it is. @Reply #1 - good point about the linear algebra, but ngl, I think statistics is actually what youll use most when youre actually looking at data. I've been sticking with No Starch Press Practical Statistics for Data Scientists 2nd Edition for a while now and I am super satisfied with how it explains things without getting too bogged down in pure theory. No complaints so far, and it really helps with the job-ready side of things. For the calculus part, dont worry about solving massive equations on paper like in school. You mostly just need to understand the concept of a gradient which is basically just how a function changes. Its what helps the models learn by finding the lowest error. I have found that Wellesley-Cambridge Press Introduction to Linear Algebra 6th Edition by Gilbert Strang is also a really safe bet if you want to be sure youre getting the fundamentals right. Its a classic for a reason and very reliable for beginners who need a solid foundation. Since youre aiming for December, just focus on the why behind the math rather than memorizing every formula. Youre gonna do fine, just take it one chapter at a time and dont let the notation freak you out. If you need more help with specific topics just shout!

Linear algebra is essential. I'm satisfied using:

• Pearson Mathematics for Machine Learning 1st Edition: Great theory, lacks code.
• O'Reilly Hands-On Machine Learning 3rd Edition: Excellent code, less math. Both work well.

Gonna try this over the weekend. Will report back if it works!

@Reply #5 - good point! It is wild how overwhelming the theory feels at first. Seeing everyone suggest the heavy textbooks is fine, but honestly, you dont need a math degree to get hired. Focus on understanding how matrix multiplication works in code rather than proving theorems. You might want to consider Strang Introduction to Linear Algebra 5th Edition if you need a deeper dive later, but for now, keep it practical. I would suggest checking out the online courses from Khan Academy since they are free and cover the exact calculus and stats gaps you have. Be careful not to get stuck in tutorial hell where you just watch videos forever. Make sure to actually build a simple model using Scikit-learn Machine Learning in Python because hands-on work is how you pick up the math naturally. Stop worrying about the Greek symbols for now; most of that stuff is just shorthand for concepts you already intuitively understand.

Late to the thread but man, I'm right there with you... the whole math as a second language thing hits way too close to home. My brain is basically mush when I see a summation sign since I haven't done a proper derivative in a decade. Being super stingy with my budget is the goal right now because those textbook prices are a total scam. Currently looking at Dover Publications Essential Calculus with Applications because those Dover books are usually like fifteen bucks. Another thing I'm eyeing is McGraw Hill Schaums Outline of Statistics 6th Edition since you can find them used for peanuts and they have tons of practice problems. Honestly trying to save my cash for a better hardware setup instead of blowing it all on paper. Glad it's not just me feeling like I'm drowning in Greek letters lol.

Can confirm