My name is Spencer Pao, and on this channel I will cover theory and applications related to Finance and Technology or both (FinTech). If you want to know how to how to implement a finance or data science/engineering application, then this is the channel for you!
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For many of my coding videos, my code is usually posted here: github.com/SpencerPao
Quant models stop working because competition replicates it. They replicate it in a certain market. Why not just move to another market in another country where that strategy is not prominent?
Thanks for the awesome tutorial! Can I connect a back-end code to any of the front-end pages of al-folio? As in, run a code in the back-end and show a simple pictorial demonstration in the front-end?
If i was to adapt this methodology to recommend songs based on user song selection, and used a dataset with parameters of a songs, how would i do that?
Good tutorial. Thanks for sharing. I have a question on the feature importance. How can we get Feature importance from XGBoost? Can you add that xgb.importance object for our reference?
Running into an issue. I follow your process and get to the point where you 'bundle install' and 'bundle exec jekyll serve'. All goes good but the locally hosted website isnt updated with my changes? I change my name, commited and pushed (verified it on my github) and its still the default confg.xml or splash page. Awesome video btw!
Commenting from two years later -- nice tutorial, bad template reference: this template is not very robust. If you are new to github page making, this is going to lead you down a deep rabbit hole where you'll end up search -> fix bug -> search -> for a long while. Caution.
So we give question as input from prompt then our model picks up a random context from our dataset and gives random answer...(if we didn't fine tune the model)
thanks for the video and the code. Just a note: you check correlation with absolute prices, instead correlation should be done between normalized prices.
Hey man, nice video, and thanks for the tutorial. I'm actually trying to build a recommendation system for online courses, like udemy, but I can't find any datasets for user reviews to make the collaborative filtering. So I decided to manually create a dataset, and thought of choosing like 4 subjects and putting some users to rate like 10-15 courses of each subject. Do you know if something like that can work, or have any tips you can give me?
Hi Spencer, could you pls help me understand why the initial GRU prediction generated a flat line? That indicates no pattern from all the years of gold prices have been “learned” by the first GRU model? Thanks.
Please create video on adding a new entity to a spacy NER model, such as DISEASE. Get the diseases from huggingface for the customizable vocabulary of diseases. Thanks.
Hi, First of all. Nice video. Very clear and worked all well on Sepolia Test NW. I'm having issues with gas fees trying to deploy on Mainnet. Any suggestions. It always tells me >> Returned error: gas required exceeds allowance (235901) >> whatever gas limit I set.
Great video! I'm encountering some errors with my own data because of the presence of different levels of a categorical predictor in the train vs test dataset. In other words, I have a categorical predictor with different levels which I encoded as dummy variables. However because of the random 80/20 split, my test data does not contain some of the levels which are present in the train data, resulting in an error when using "predict". Do you have any tips on how to go about this? (also in case of z-scoring/ calculating standardized residuals in advance for some variables, I suppose scaling isn't necessary anymore for those variables?). Cheers!
Hello, I have a larger set of data around 31192 observations and 13 variables, i want to do the K and HC analysis? Can ou please help me regarding this, I tired a lot but couldn't? Is it possible can you to give me your email?
