Easy class bc you get tested on useless things. Literally don't understand why people love Miles, I've had minimal interactions with him but when I have interacted with him, he's pretty rude and sassy. He makes you feel small. Yes, I understand that he wants to spend some lecture giving lectures on life and shiz but also I WANT TO LEARN SOME USEFUL STATS MATERIAL. class is a joke

Easy A. Learned nothing. I literally finished this course less than three weeks ago and I cannot remember a thing about it.

I do recommend Chen though; he's a solid human being. Which we need more of these days lol

Summer session for 102B was pretty watered down, skipped a lot of proofs and the final chapter on PCA. Lectures were all uploaded to YouTube but attendance was required. Felt like I didn't learn much about applying ML techniques for extensive data analysis but got an easy A. Lectures were a bit rushed and unclear on neural l networks since summer had limited time. HW seemed unchanged from previous years as there were issues with R version above 3.0 , which was addressed very late into the session. A bit disappointed in the lack of interest/input

I took the entire 102 series with Miles, and I have to say he is one of the clearest professors in the stats department. You can completely follow him and figure out what he expects after one quarter with him.

So this is kinda a review for the entire 102 series with Miles. 102A is mostly about coding, and he taught useful coding techniques and fun staff in class. There was a tic-tac-toe project and a monopoly project that are time-consuming (took me about one day for each) but are really accomplishing when you finish.

102B is the most math heavy, and all the matrix notations are kind of overwhelming at the very beginning. However, Miles really explains all the different machine learning methods out in a way that is easy to understand, and I have to say it is very helpful to have known different machine learning concepts when interviewing for researches.

For me, 102C is the easiest among the entire series. Just follow Miles' hand-written notes in class, and you would be fine.

Miles is also helpful in his office hours (He helped me a couple of times when it wasn't really his office hours but he happened to be in the office!) Also his office is super organized, and I was impressed LMAO.

Generally I really recommend Miles for STATS 102 series.

Maybe Professor Chen revamped the class this quarter (so maybe the topics are different now), but I thoroughly enjoyed 102B and thought the curriculum wasn't scattered at all. It's a digestible, effective introduction to popular machine learning concepts and algorithms for constructing models and conducting analysis. No curveballs on the exams, it all depends on how much effort you put into preparing for them. Professor Chen comes to class everyday with a smile on his face, and he does a wonderful job preparing you with a solid foundation and intuition for the course material in case you want to explore any of them in greater detail, and that's honestly all the space there is for a 10 week class. Had a blast this quarter, thanks Professor Chen! :)

Professor Chen is one of my favorite professors at UCLA. His lectures are very clear and assignments are designed to help students understand the materials. The concepts and algorithms covered in this class are very useful and practical. Overall, I highly recommended this class.

Miles has changed, and I hope he's doing alright frankly. Awesome guy I still believe but he's not Smiles Chen at this point in time, I'll say. This class, in particular-- I have no idea what the curriculum even was, as he just bounces randomly around topics. Most unclear course curriculum I've ever taken by far. I actually cannot tell you what it was about in like than 6 sentences. Most pointless and unclear stats course thus far for me.

It's pretty much impossible to dislike Professor Chen, as a person as well as a professor. He's just such a nice, caring guy who does a great job of teaching the 102 series. He's also super laid-back. I've been fortunate to have many great professors during my time at UCLA, but he is definitely one of my favorites.

Great Professor! Interesting class as well, with a focus on coding in R.