## 🚢 Titanic Survival Prediction – Final Model!
I trained and fine-tuned a RandomForestClassifier to predict Titanic survivors. After tweaking the model, i tried to implemet the things that i was talking here tbh it feels so nice actually this is the first dataset i handled on my own , and i'm sure i'll do more. here are the final results:
✅ Accuracy: 83.24%
✅ Precision: 0.84 (Fewer false positives)
✅ Recall: 0.73 (Decent survivor detection)
✅ F1 Score: 0.78
✅ AUC Score: 0.814
🔹 False positives dropped to 12 (from 15)
🔹 False negatives stayed at 19
📌 Next? Maybe test other models like XGBoost or ensemble methods. Let me know if you want a breakdown! 🚀
#MachineLearning #Titanic #DataScience
I trained and fine-tuned a RandomForestClassifier to predict Titanic survivors. After tweaking the model, i tried to implemet the things that i was talking here tbh it feels so nice actually this is the first dataset i handled on my own , and i'm sure i'll do more. here are the final results:
✅ Accuracy: 83.24%
✅ Precision: 0.84 (Fewer false positives)
✅ Recall: 0.73 (Decent survivor detection)
✅ F1 Score: 0.78
✅ AUC Score: 0.814
🔹 False positives dropped to 12 (from 15)
🔹 False negatives stayed at 19
📌 Next? Maybe test other models like XGBoost or ensemble methods. Let me know if you want a breakdown! 🚀
#MachineLearning #Titanic #DataScience
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and Mid-exam in a week so time to study before I get cooked again😅
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Forwarded from Dave Dumps
living means choosing. But do we always choose freely and consciously ? is our choice not frequently forced on us by circumstances, by our faint-heartedness, our habits or even our guilts ?
~ Dr. Paul Tournier ( Guilt & Grace - Matters of Time)
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Midnight silence isn’t just the absence of noise—it’s a presence. A quiet so deep it feels alive, wrapping you in its calm, making the world feel both infinite and intimate at the same time.
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Media is too big
VIEW IN TELEGRAM
mann I love this stg It’s the kind of quiet that doesn’t feel empty but full—full of thoughts, emotions, and the weight of the night
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ቆይ አንዳንድ ሠዎች ማርፈድ በደማቸው ነውንዴ ያለው like fr እህህህህ specially demo የኛዎቹ literally everyone i know is አርፋጅ weys their clock runs on a different timezone than the rest of us? ወገን atleast Let’s try to sync up የምር ያስተዛዝባል😭
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Robi makes stuff
Bout to take another picture , say cheeseeeeee 📸
From messy datasets to smart models—learning never stops!
#TGYearBook25
#TGYearBook25
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Machine Learning from Scratch by Danny Friedman
This book is for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different algorithms create the models they do and the advantages and disadvantages of each one.
This book will be most helpful for those with practice in basic modeling. It does not review best practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
🌟 Link: https://dafriedman97.github.io/mlbook/content/introduction.html
This book is for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different algorithms create the models they do and the advantages and disadvantages of each one.
This book will be most helpful for those with practice in basic modeling. It does not review best practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
🌟 Link: https://dafriedman97.github.io/mlbook/content/introduction.html