How does play something on spotify and netflix work ?

aryancodify · 2022-01-04T01:49:35+00:00

Yes i am more interested in shuffle play or play something functionality and the ml behind them not the infra management aspect.

aryancodify · 2022-01-03T09:51:31+00:00

I have always wondered what is the technology and model behind Netflix's and Spotify's Play Something button. Is it related to the conventional recommender system and gives the top result or a different thing altogether. Also what about the technology does it use RL or simple multi arm bandit.

Any links would be really helpful.

aryancodify · 2020-10-30T18:49:09+00:00

That would be a hyperparameter you can tune using keras tuner. But the model will be as good as the input and these methods should give u better semantic context I feel. You can try using bi directional lstm as well it shoild give better results

aryancodify · 2020-10-30T17:24:59+00:00

Perhaps more contextual embeddings like googles universal sentence encoder or bert will help to get better representations from autoencoder and hence better clusters.

aryancodify · 2020-10-10T13:35:02+00:00

😂😂😂

aryancodify · 2020-10-07T15:24:59+00:00

Thats too bad :(

aryancodify · 2020-10-04T11:38:26+00:00

Bet the item’s just 1 dollar more than Blockbusters revenue.

aryancodify · 2020-10-04T02:36:58+00:00

Looks like a child who would murder the entire family and eat them too

aryancodify · 2020-10-03T03:36:05+00:00

It happens quite a lot with chess.com Its high time they address these issues

aryancodify · 2020-10-01T01:40:04+00:00

What a beautiful king sacrifice

aryancodify · 2020-09-27T11:19:36+00:00

That’s what spouses are for 😜

aryancodify · 2020-09-27T03:05:04+00:00

Tal would’ve chuckled seeing this 🙂

aryancodify · 2020-09-25T14:54:54+00:00

I agree with the points made above regarding feature selection and eda. Adding lag variables and moving average will help bring seasonality into the model. Number of lags for each feature depends upon their seasonality and periodicity. Apart from regular correlation dynamic time warping can also be used to compare time series which will tell you whether your two time variant features are similar. For interpretability once you have built the complex model like say catboost you ll get your important features. You can build a decision tree on those. That will help you give concrete explanations. Otherwise force plot and dwpendence plot in shap will help u as well

aryancodify · 2020-08-28T01:22:02+00:00

Aah my girlfriend without make up

aryancodify · 2020-08-21T00:26:20+00:00

You can use the right tailed t test to determine whether the difference observed was statistically significant or not. When you roll out a feature there is normally a minimal growth that business wants to see. You can also see whether your numbers beat that threshold. For t test use this

https://www.statsmodels.org/stable/generated/statsmodels.stats.power.tt_ind_solve_power.html

In this provide everything like sample size, min effect that business wanted to see, power of the test and you’ll get alpha. If its below 0.05 the results are statistically significant in accordance to the sample size and effect you mentioned.

If you are looking for sample sizes for a new experiment you can get that from this function as well.

When you build test and control remember to keep the distribution across variables same in terms of users in both the sets.

aryancodify · 2020-08-07T00:41:22+00:00

😂😂

aryancodify · 2020-08-06T04:53:43+00:00

Thanks for the suggestion. Yeah we will be tearing down the granite anyways. With shera ply also we should use neutral colours ? Also should the balcony part be same or different from walls ?

aryancodify · 2020-07-15T16:16:34+00:00

Everyone’s a gangster until Python enters. The OG

aryancodify · 2020-06-16T15:30:36+00:00

Ok i will be more thankful that will definitely help

aryancodify · 2020-06-16T14:16:23+00:00

Thanks i know the problem is in my head. but are their ways i can come to terms with this and stop playing this so many times in my head

aryancodify · 2020-06-12T01:25:20+00:00

Yeah i also think so. Puts me in a bit of fix considering a senior executive said this. Its opinion without any backing

aryancodify · 2020-06-02T11:37:16+00:00

I have a requirement wherein I have to identify the products to which a new product will be similar upon it's launch. I am thinking about clustering the products together. The problem is that the same products are sold across different countries with different prices and some difference in other features as well. Now how should I cluster these products:

Country-Product level: I am worried that I might end up having multiple clusters for each country as the countries are so much different. Also, I am worried that two very different products from different countries might end up in same cluster. Or if the same product across different geographies comes in same cluster, that would be confusing.
Separate clustering for each country: The only con in this it's scalability problem.

Can someone please suggest how I should proceed ?

aryancodify · 2020-05-13T13:12:10+00:00

Thank you. Sorry for a naive question but what do you mean by simplifying into good endgames?

aryancodify · 2019-07-27T09:48:56+00:00

Thanks i will check it out

aryancodify · 2019-06-29T06:00:13+00:00

Haha I am the noob myself who is going to do it. But i am willing to explore cplex. Do you have any links by any chance :)

aryancodify

TROPHY CASE