Alrighttt the break is over lemme get back to tuning them hyperparameters
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Hoping you find strength as you look to what was done on the cross
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Mike's ML Forge
2. How to Know Which Columns Are Useful? Here are every possible way to decide which features matter: A. Correlation with Target Variable (for regression) Check how each feature correlates with the target (label). df.corr()['target_column'].sort_value…
B. Feature Importance (for tree models)
Use models like RandomForest or XGBoost to get importance scores.
Use models like RandomForest or XGBoost to get importance scores.
from sklearn.ensemble import RandomForestRegressor
model = RandomForestRegressor()
model.fit(X, y)
importances = model.feature_importances_
# Show them in a DataFrame
feature_scores = pd.DataFrame({'Feature': X.columns, 'Importance': importances})
feature_scores = feature_scores.sort_values(by='Importance', ascending=False)
print(feature_scores)
Forwarded from Tech Nerd (Tech Nerd)
Imagine Barabbas — the criminal who was supposed to be crucified. He was guilty, no question about it. But at the last moment, the crowd shouted for Jesus to take his place, and Pilate released Barabbas (Matthew 27:16-26). Think about that: an innocent man took the punishment meant for the guilty, and the guilty man walked free. Barabbas didn’t earn it, didn’t ask for it — yet he was set free because Jesus was condemned.
That’s the heart of Easter. Just like Barabbas, we were guilty — our sin deserved judgment. In the Old Testament, the law reminded people of this constantly. But Jesus stepped in, not just to cover our guilt like sacrifices did, but to take it on Himself and remove it entirely. As Colossians 2:14 says, He nailed our record of wrongs to the cross. Easter isn’t just about Jesus rising from the dead — it’s about Him switching places with us, paying our debt, and giving us His freedom. Barabbas walked off the platform a free man. So do we, because of Easter.
@selfmadecoder
That’s the heart of Easter. Just like Barabbas, we were guilty — our sin deserved judgment. In the Old Testament, the law reminded people of this constantly. But Jesus stepped in, not just to cover our guilt like sacrifices did, but to take it on Himself and remove it entirely. As Colossians 2:14 says, He nailed our record of wrongs to the cross. Easter isn’t just about Jesus rising from the dead — it’s about Him switching places with us, paying our debt, and giving us His freedom. Barabbas walked off the platform a free man. So do we, because of Easter.
@selfmadecoder
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Mike's ML Forge
B. Feature Importance (for tree models) Use models like RandomForest or XGBoost to get importance scores. from sklearn.ensemble import RandomForestRegressor model = RandomForestRegressor() model.fit(X, y) importances = model.feature_importances_ # Show…
C. Statistical Tests
Depending on the type of data:
Numerical vs numerical? → correlation
Categorical vs numerical? → ANOVA / t-test
Categorical vs categorical? → Chi-Squared test
Depending on the type of data:
Numerical vs numerical? → correlation
Categorical vs numerical? → ANOVA / t-test
Categorical vs categorical? → Chi-Squared test
How to Improve a Predictive Model?
1. Evaluate Performance
Compare with a baseline model (simple predictor).
Check key metrics (accuracy, RMSE, etc.).
2. Improve Data
Collect more data if possible.
Clean, preprocess, and engineer better features.
3. Choose a Better Model
Try different algorithms (e.g., Decision Trees, SVM, Neural Networks) we'll see them in future
4. Tune Hyperparameters
Adjust settings like learning rate, tree depth, or batch size.
•Use GridSearchCV or •RandomizedSearchCV for optimization.
5. Prevent Overfitting & Underfitting
•Overfitting? Regularization, dropout, or pruning.
•Underfitting? More features, deeper models.
Optimize these steps, and your model will improve!
1. Evaluate Performance
Compare with a baseline model (simple predictor).
Check key metrics (accuracy, RMSE, etc.).
2. Improve Data
Collect more data if possible.
Clean, preprocess, and engineer better features.
3. Choose a Better Model
Try different algorithms (e.g., Decision Trees, SVM, Neural Networks) we'll see them in future
4. Tune Hyperparameters
Adjust settings like learning rate, tree depth, or batch size.
•Use GridSearchCV or •RandomizedSearchCV for optimization.
5. Prevent Overfitting & Underfitting
•Overfitting? Regularization, dropout, or pruning.
•Underfitting? More features, deeper models.
Optimize these steps, and your model will improve!
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Hyperparameters are settings on a model you can adjust to improve its ability to find patterns
Parameters are patterns that the model finds in the data
Parameters are patterns that the model finds in the data
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Forwarded from ᴏᴇᴜᴠʀᴇ 𐌓ₑ ᴋɪᴅᴜꜱ (ቅ𝔡𝔲ስ)
The Illusion of Being Put Together
Everyone looks like they’ve figured it all out...
Spoiler: they haven’t. It’s just good angles and practiced captions. Meanwhile, authenticity is quietly dying in everyone’s drafts.
#random_k
@oeuvre_de_kidus
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Forwarded from Journey Log⚡️
"I’m a university lecturer.
I was the top scorer in the Grade 12 national exam in my stream—possibly the highest of all time. I graduated with a perfect 4.00 GPA, the only one to do so at my university to date. I completed my master's degree at Addis Ababa University with very great distinction. I was considered the best of my generation. But truthfully, every university lecturer was once the best of their generation.
I've been teaching for seven years now. My net salary is 10,700 Birr. I pay 7,000 in rent and survive on the remaining 3,700. It feels less like a profession and more like a punishment for excelling in school.
Now, I’m expected to inspire my students—standing in front of them in worn-out shirts and uneven shoes, trying to convince them that hard work pays off. I was supposed to be a symbol of excellence, someone they could look up to. Instead, I’m a cautionary tale.
Meanwhile, cheaters, corrupt officials, and unqualified party loyalists reap the rewards of a broken system. This country doesn’t belong to them—it belongs to those who built it with knowledge, sweat, and service. It’s time to reclaim it from the parasites and restore dignity to those who earned it."
I was the top scorer in the Grade 12 national exam in my stream—possibly the highest of all time. I graduated with a perfect 4.00 GPA, the only one to do so at my university to date. I completed my master's degree at Addis Ababa University with very great distinction. I was considered the best of my generation. But truthfully, every university lecturer was once the best of their generation.
I've been teaching for seven years now. My net salary is 10,700 Birr. I pay 7,000 in rent and survive on the remaining 3,700. It feels less like a profession and more like a punishment for excelling in school.
Now, I’m expected to inspire my students—standing in front of them in worn-out shirts and uneven shoes, trying to convince them that hard work pays off. I was supposed to be a symbol of excellence, someone they could look up to. Instead, I’m a cautionary tale.
Meanwhile, cheaters, corrupt officials, and unqualified party loyalists reap the rewards of a broken system. This country doesn’t belong to them—it belongs to those who built it with knowledge, sweat, and service. It’s time to reclaim it from the parasites and restore dignity to those who earned it."
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