youngprogrammer

5 ms·

1.
by youngprogrammer 3mo ago
At a 3 minute shot, I’d rather use the same time to do a pour over
2.
by youngprogrammer 4mo ago
You might as well play "who can memorize the most openings and lines"
3.
by youngprogrammer 4mo ago
It can get complicated quickly if you're actually using it in a production system. At my prev enterprise saas company we had feature flags that could be turned on per customer / per environment (dev, staging, prod) with permission
4.
by youngprogrammer 4mo ago
this is essentially how bindcraft works for drug discovery: https://www.nature.com/articles/s41586-025-09429-6 (minus the accumulation step) feedback from af2 folding confidence + structural scoring
5.
by youngprogrammer 5mo ago
Fish sauce is delicious but had to stop using it since it's high in histamine (gives me a stuffy nose) and potentially carcinogenic due to its high levels of nitrosamines
6.
by youngprogrammer 6mo ago
industrialized overfitting is basically what ML researchers do
7.
by youngprogrammer 7mo ago
should go a bit earlier with word2vec, NMT, seq2seq, attention, self attention
8.
Scientists Contact Whales in World-First Communication Experiment(businessinsider.com)
1 points by youngprogrammer 3y ago|0 comments
9.
by youngprogrammer 3y ago
Little late to this thread but from my list: LLM (foundational papers) * Attention is all you need - transformers + self attention * BERT - first masked LM using transformers + self attention * GPT3 - big LLM decoder (Basis of gpt4 and most
10.
by youngprogrammer 5y ago
It seems like most of these imperceptible changes could be addressed by something like ascii folding ( https://www.elastic.co/guide/en/elasticsearch/reference/curr... ) but this might not apply for non-eng
11.
by youngprogrammer 6y ago
They probably didn't have a Gantt chart to help them figure out the dependencies to properly plan it on their roadmap
12.
by youngprogrammer 6y ago
You could do something similar to how they trained a ML model to find antibiotics compounds: https://www.cell.com/action/showPdf?pii=S0092-8674%2820%2930... . First, train a deep learning model to learn a representation
13.
by youngprogrammer 7y ago
Anecdote: Our caterer in silicon valley said there was a supply issue for tofu.
14.
Video of Combat Robots Flagged as Animal Abuse(support.google.com)
1 points by youngprogrammer 7y ago|0 comments
15.
Show HN: Num2vec – Numerical Embeddings via Deep Nested RNNs(blog.ayoungprogrammer.com)
6 points by youngprogrammer 9y ago|0 comments
16.
by youngprogrammer 9y ago
This is nothing like the sharpshooter fallacy. The analysis determined the average performance of the analysts with >100 stocks rated and 10 analysts out of 16 did better than the rest.
17.
by youngprogrammer 9y ago
How do you measure top ten if you don't have a ranking system?
18.
by youngprogrammer 9y ago
Top 10 performers out of 16 or so analysts in the analysis is not survivor bias.
19.
by youngprogrammer 9y ago
Outliers were removed to get a better measure of the "accuracy" of the price targets. 10 day windows were used to reduce the amount of volatility/noise in a time frame Return horizons for 1 years was used because price target
20.
by youngprogrammer 9y ago
I will agree that the methodology is not as rigorous as it could be but where can you prove it is "wrong"? My blogpost shows that stock price predictions also show a terrible track record. They are wildly off and on average higher
21.
by youngprogrammer 9y ago
I probably should have included the outliers when analyzing overall performance but if I recall correctly they did not have a significant effect. The top analysts were determined by the average performance from one year after their ratings
22.
by youngprogrammer 9y ago
You're correct that I should have accounted for outliers when measuring performance of this strategy. If I recall correctly, even with the outliers, they did not significantly affect the average performance of analyst ratings. I would
23.
by youngprogrammer 9y ago
Hey Matthew, thanks for running your website! It was very helpful for obtaining the data I needed for my blogpost.
24.
by youngprogrammer 9y ago
In my analysis, I do hypothesize that analyst opinions become a self-fulfilling prophecy as you described. However, I would like to believe that analysts do some sort of sophisticated breakdown and analysis of a company's financial sta
25.
by youngprogrammer 9y ago
1. Removing outliers was for making the data easier to analyze as some outliers were skewing the average. Of course when investing you cannot ignore outliers, but you could possibly curb them with stop losses/stop limits. 2. A more in-
26.
by youngprogrammer 9y ago
Unfortunately, the website I used to scrape the data only had 2 years of data. But each datapoint is looking at each individual analyst rating and price target for a stock and then comparing it to the price in 1 year. However, you are corre
27.
Stocks with Outperform Ratings Beat the Market(blog.ayoungprogrammer.com)
119 points by youngprogrammer 9y ago|65 comments
28.
by youngprogrammer 9y ago
How to travel like a millionaire? Ask the millionaire
29.
Show HN: Using Python and Pandas to Analyze Price Targets and Ratings(blog.ayoungprogrammer.com)
4 points by youngprogrammer 9y ago|0 comments
30.
by youngprogrammer 10y ago
Demo should be working now. The stanford parser getting dying from running out of memory so I moved it to a another box

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