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**Description:**
Hello, I am new on deepchem and deeplearning.
I would like to understand something, I train a model from the membrane_permeability example, for this dataset we load the sdf data and…
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Based on @kongzii suggestion:
-> Divide all agent's predictions into probabilty buckets (deciles), e.g. if an agent gives 65% probability to a market, it goes in the 7th decile.
-> For each decile…
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Description: Develop a neural network-based system to provide highly accurate property valuations based on a wide range of factors and historical data.
Tasks to Accomplish:
Design the property v…
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Create an agent that doesn't make predictions based on research, but instead looks for arbitrage opportunities (2 +ve/-vely correlated markets with differntly correlated market p_yes values).
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Trying to get predictions using the ReadME tutorial and getting the below error during run_prediction.py
```
09/23/2024 21:12:42 - INFO - __main__ - ***** Running prediction *****
09/23/2024 2…
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**Github username:** --
**Twitter username:** --
**Submission hash (on-chain):** 0xdfac576e411c1ebe8821865e66f24df26a1ad484c44671a60f134ed11c6901c6
**Severity:** high
**Description:**
**Description*…
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**Is your feature request related to a problem? Please describe.**
Yes, it will provide valuable insights into applicants' financial metrics and loan approval outcomes, as well as understanding the f…
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Hi, thank you for your awesome work!
There is a question about the final prediction result of lvu_cls. I have found that in your code, the evaluation process are based on the prediction result of im…
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Hi can you give a sample implementation on how to run your model on specific user input from the pre-trained models? Can you guide with the demo pipeline to predict aspect sentiment for a user input i…
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