u/Physical_Yellow_6743

Good day. I am currently taking an NLP course. However, I need help to understand what am I really learning.

I learn that one-hot vector is processed by an embedding matrix to convert it to dense vectors so that similar words can be compared with one another. However, the lecturer suddenly talked about Word2Vec, window-based co-occurence matrix and SVD, and GloVe.

However, I am confused as in why am I learning all these stuff. Like Word2Vec essentially takes the dot product of dense vectors from a training pair generates a score => softmax function converts the score to probability => probability used to generate log of likelihood function => negative average likelihood function is a loss function where we want to minimize it by maximizing log likelihood. But then what?? So what if I achieve all that?

Next, window-based co-occurence matrix gives me a matrix with counts of how many word-context pairs are there. Use SVD to generate a word embedding? Didn't we generate the dense vector earlier?? I don't get what am I using this for again?

Lastly, GloVe basically gets the ratio of the conditional probabilities. Ok... but why do I do this for...

Then the lecturer said they are word embedding methods and I was like didn't you mention you use dense vectors to calculate the scores? Why we need to generate an embedding table to multiply with the one-hot vector to get dense vector again? However, he couldn't reply to my question because of a language barrier... Hence... I really hope to seek clarifications.

Hi. I got an offer for an internship and was wondering how long it will take for NUS to process LOA. I understand that if LOA is applied prior to week 2, I would not need to pay for school fees. However, the company I applied for wanted to know when is my earliest available date and I am not sure if I should apply for LOA and go for my internship or have to wait for NUS to approve the LOA first.

Hi. I am currently an undergraduate in data science. I have learned things like coding, statistics, and mathematics. However, I realise that I tend to forget the majority of what I learned over time when I start a new semester. Even if I have learned them during the break, I will eventually forget them. For instance, in one interview I had, I have talked about a multiple regression project that uses hypothesis t-test and F-test to determine significant regressors and models, residual analysis, multicollinearity checks using correlation analysis, VIF, Eigensystem analysis, cook's distance for detecting influential points, AIC etc. but then if he asked like how did you derive the response as log y.... I said something like box cox method... but I kind of forgot the formula, just that we basically fit the new y to the data, find the lambda that produces the lowest SSRES since they result in MLE's lambda, and then fit log y if lambda = 0. Hence, I am just wondering, as there are more advanced statistics and technical skills to learn in the future, how do you remember all your stuffs? What if you forget about it on the job?

Edit: hi. Thanks for all of your replies! I find it comforting knowing that it’s a common occurrence to forget some things at times. But, just wondering, if the interviewer asked something I forgot, what’s the best course of action?

Hi seniors. I hope that you are all doing well. I am currently an undergraduate, and I have knowledge in machine learning models and statistics. Hence, I usually do exploratory data analysis and create predictive models using Python and R. I have knowledge in Excel, in areas like power query, pivot tables, functions like xlookup sumifs etc. I recently got an online retail data from the ucsi repository and I want to work towards producing an interactive dashboard that displays sales and customers information. However, I was wondering what do you all usually look out for when doing Excel Analysis. Earlier in the day, I have cleaned the data using power query and xlookups to fill up missing product names so I’m fine with that part. Thank you.

Edit: Hi. Thanks for the responses so far. The reason why I am doing this project is to showcase my Excel skills as previously most data I have worked with in Excel is more for practice rather than to do something solid. I would like to showcase that I can use Excel as a tool to drive business solutions, with parameters used in the real-world scenarios. Hence, I was wondering, based on all of your experiences, doing data analytics in your respective industries, what I should really focus on when deriving informative insights and delivering meaningful solutions.

Hi. I am planning to take IT1244 to fulfil the AI requirements next semester, and was wondering what the best module combinations to take with it are. Currently, I am left with 1 HS29XX, 1 GEN, DSA3101, DSA3102, CS3244, and I plan to take 2 DSA42XX modules + internship (still finding). Thanks.

Hi. I am a DSA major and I was wondering if doing these 3 modules together with a chs common mod is advisable: CS3244, DSA4213, IT1244 (AI common mod, seems interesting compared to the others).