Free Humanity from Mathematics (Basic Algebra Edition)

I gave up on math, but math didn't give up on me. It was easy.

Please tell me how middle and high school math can be applied to machine learning and deep learning along with background knowledge. The class progress is dense and quite fast, so if you lose your mind, you have to listen to it again. - [Review after completing more than 50% of the class progress] 1. Course background I am a liberal arts graduate and working person who started studying math to change my career path. In particular, considering preparing for the GRE, I needed middle and high school math skills, but I was worried that I did not have enough, so I took Professor Shin Kyung-sik's class. 2. Class style The class progresses very quickly, and since it focuses on only the necessary parts, you need to concentrate every hour. Also, if you do not consistently review and acquire the example problems attached to the lecture notes, you may not be able to fully utilize what you learned in class, so I think it is important to put a lot of effort into this part. 3. Class content For those who want to study artificial intelligence/data science, I highly recommend Professor Shin Kyung-sik's class over EBS. This class gives you the feeling of going over middle and high school math at once, but also implicitly explains how it can be applied to machine learning and deep learning, so if you study it together with PyTorch or NumPy basics, you will naturally realize the need for algebra basics. Also, when preparing for an AI/data science major, you will deal with a lot of English, and it was very helpful that the teacher explained the mathematical terms in both Korean and English. In addition, this algebra class helped me reduce the vague stress and fear of formulas, as I used to feel burdened when reading papers because I couldn't understand the formulas. The teacher explained everything step by step, so it was very helpful because I was able to gradually understand the formulas. Overall Review This class is fast-paced but systematically organized, and is very useful for building the mathematical foundations necessary for an AI major.

Impressions during the class 1. Amazing compression and delivery power that losslessly compresses content that would normally take 2 hours into 10 minutes. 2. The biggest obstacle I face while relearning high school level math is that I have to endure boredom because it is something I can understand if I listen to it, but the background explanation related to the field never gives me time to get bored. 3. Since the lecture terms are in English, the pre-learning effect is a bonus for me who plans to read math-related original books at night. Why did the heavens send me an engineering major now...

The lecture is really good, but... I was busy with my main job and the lecture expired while I was not able to attend... Is it possible to extend it? Also, I wonder if you have any plans to change it to unlimited.

I bought the lecture because I wanted to organize math again while studying data science, but the instructor speaks very well and the flow is not interrupted and it goes right into my ears. Even though he speaks fast, his pronunciation is accurate and he doesn't necessarily have to speed up the playback speed, so I just put it on 1x and watch it. I wish there was a 0.75x playback speed for Inflearn. It's a really concise explanation. This lecture saves me time😆 And what's even better is that he explains the core theories in a standard way while mixing in easy examples here and there, so I thought the latter part was a bit difficult, but he explained difficult concepts so easily that I thought, "Hmm... I can do it?" They say that geniuses are not geniuses because they solve difficult things easily, but the instructor seems to be a real genius and I think he's done a lot of research. Thanks to him, I think I'll be able to build a solid basic base. The lecture title is also really perfect🍡

I feel like it's different from the math I've been learning~! In addition, since you explain it from a different perspective (like deep learning), I feel like I'm understanding some principles. Thank you for making a great lecture, and as you mentioned in the roadmap, please make sure to do future math lectures on vectors/linear algebra, etc. (It seems like you're busy with other lectures.. When can I see the next math lecture..?)

I love it! Please do probability statistics, linear algebra, and calculus!

I know that they extend it once, but can I ask for an extension? The lecture was really good, but I couldn't listen to it all because of family matters.