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This project seeks a set of Ghidra import regression tests to validate sensible behavior after importing executable binaries into new versions of Ghidra. It's morphed somewhat into generating newer e…
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When training Scikit-learn models I noticed that the code finishes significantly faster in a normal cell. When running the same function in a JupyterDash app, it takes up to 20% more time to finish.
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VNDRN updated
4 years ago
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We can use AdaGrad + SGD to support basic basic regression modeling relating a dense vector of predictors to a univariate outcome:
- [x] ApproxOLS
- [x] ApproxLogit
- [ ] ApproxRidge
- [ ] ApproxL2Log…
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Here is an outline with a todo list for various sections. Please edit as needed and update status. They can be checked off if they are mostly there, as I'm sure we will tinker until the course starts.…
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We can solve Binary and Multi-Class classification problems with the help of algorithms like Logistic Regression, Support Vector Machines, Random Forest, etc. So to solve the present Multi-Label class…
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from: https://github.com/llvm/llvm-project/commit/8ac924744e93258d0c490e2fa2d4518e24cb458d
to: https://github.com/llvm/llvm-project/commit/f73050e722dd2e484358d03674eb186f3a2f4799
commit: 72304586324c…
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# Import necessary libraries
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import Multin…
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Hi, I saw your Support_Vector_Regression_(SVR).ipynb, Good Work, just one comment:
If you apply MinMaxScalar on time series, in this case, it will introduce the bias in the variables. Result will …
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Below are some places to look at to see what kinds of topics should be covered. Comment below for what you think should be covered in the series of videos. Topics can range from simple to complex.
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- [ ] [Release Release 2.0.0 stable · dmlc/xgboost](https://github.com/dmlc/xgboost/releases/tag/v2.0.0)
# Release Release 2.0.0 stable · dmlc/xgboost
## Snippet
We are excited to announce the rele…