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I'm taking this class now. I've finished the first two weeks of the first course and am about to begin the first set of programming assignments. Some initial

I'm taking this class now. I've finished the first two weeks of the first course and am about to begin the first set of programming assignments. Some initial impressions: - I really like Andrews teaching style, which is why I took the course. If you are familiar with his machine learning coursera class and enjoy it, you will enjoy this as well. It really feels like a seamless continuation of the ML course and the concepts taught there are helpful. You may want to go through that course first to learn the basics, but if your math is solid you can jump right in to this. - the course teaches python, numpy, and tensorflow. Some folks had trouble with Octave in the ML course, so many will appreciate the stack being taught here. - there is lots of foundational mathematics. Some like that (I do) and some don't. If you are not interested in core calculus or linear algebra details and just want to learn applied deep learning through code, you may enjoy the fast.ai courses more (which to me felt a bit cargo culty) - it's still early in the specialization for me so take the above with a grain of salt!

Edd314159 9y ago
Do you know of any courses that will bring one up to speed on the math component? I really love this format of learning, and I want to take this course as it's something I'm interested in and I like Andrew Ng, but the Week 2 content was a complete non-starter for me. I've been writing software professionally for a decade now, but because I have no mathematical background I'm very far from understanding even the first step of this course (which really is Week 2, Week 1 is just a formality).
- sonabinu 9y ago
  Get familiar with linear algebra. What I did was go back to school ( community college for cal2, linear algebra, differential equations and multi-variable calculus. ) I'm comfortable with the math now. It's a commitment for about a year but really worth your time.
- imakecomments 9y ago
  Audit edx's Calculus sequence, taught by MIT. The courses are: Calculus 1A, 1B, 1C. You can watch MIT OCW's Linear Algebra course with Strang and/or enroll in: "Linear Algebra - Foundations to Frontiers" on edx. Use Khan academy for supplemental Calculus & Linear Algebra review. You can get Stewart's Calculus text and read through it/attempt the problem sets. Once you have a solid Calculus/Linear Algebra review you can take a look at: "Statistics 110: Probability" which is found free here: https://projects.iq.harvard.edu/stat110/home https://projects.iq.harvard.edu/stat110/home.
- binarymax 9y ago
  You may just want to try Andrews original ML course. There is some introductory calculus and linear algebra early on that is solidified through the 11 weeks, and it is all in context. I didn't come into that course cold, but it had been 18 years since I took any calculus and didn't remember much...but everything I needed was taught there. The good thing about the ML course is that if a concept is taught, you know exactly what the context is and can do some further research on the side through youtube, Kahn academy, or other resources. If you had high school algebra, then with some rigor you could get through the ML course and walk away with a great foundation.
- jnwatson 9y ago
  For specific issues, I've found Khan Academy to be quite useful.

Edd314159 9y ago

Do you know of any courses that will bring one up to speed on the math component? I really love this format of learning, and I want to take this course as it's something I'm interested in and I like Andrew Ng, but the Week 2 content was a complete non-starter for me. I've been writing software professionally for a decade now, but because I have no mathematical background I'm very far from understanding even the first step of this course (which really is Week 2, Week 1 is just a formality).

sonabinu 9y ago
Get familiar with linear algebra. What I did was go back to school ( community college for cal2, linear algebra, differential equations and multi-variable calculus. ) I'm comfortable with the math now. It's a commitment for about a year but really worth your time.
imakecomments 9y ago
Audit edx's Calculus sequence, taught by MIT. The courses are: Calculus 1A, 1B, 1C. You can watch MIT OCW's Linear Algebra course with Strang and/or enroll in: "Linear Algebra - Foundations to Frontiers" on edx. Use Khan academy for supplemental Calculus & Linear Algebra review. You can get Stewart's Calculus text and read through it/attempt the problem sets. Once you have a solid Calculus/Linear Algebra review you can take a look at: "Statistics 110: Probability" which is found free here: https://projects.iq.harvard.edu/stat110/home https://projects.iq.harvard.edu/stat110/home.
binarymax 9y ago
You may just want to try Andrews original ML course. There is some introductory calculus and linear algebra early on that is solidified through the 11 weeks, and it is all in context. I didn't come into that course cold, but it had been 18 years since I took any calculus and didn't remember much...but everything I needed was taught there. The good thing about the ML course is that if a concept is taught, you know exactly what the context is and can do some further research on the side through youtube, Kahn academy, or other resources. If you had high school algebra, then with some rigor you could get through the ML course and walk away with a great foundation.
jnwatson 9y ago
For specific issues, I've found Khan Academy to be quite useful.