readme.md

Day 34 of #100DaysOfCode

Task

1. Titanic dataset prediction challenge
2. Global Hack Week challenges

Resources

• Kaggle Titanic - Machine Learning from Disaster

• • My Notebook 1
• • My Notebook 2
• • My Notebook 3

• MLH - Global Hack Week INIT 2023 hackathon

• • 2022-Goal-sticker
• • Bob Ross MS PAINT
• • Code in Python
• • A project that uses Dataset
• • Show off Github Activity
• • Random Number Generator

Topics I have learnt

1. Titanic dataset prediction

• 1st with XGBClassifier and did Feature Engineering using Mutual Information and by creating new features.
• 2nd same as above but added more columns.
• 3rd with RandomForestClassifier and did Feature Engineering by creating new features & Mutual Information.

2. Also participated in MLH Global Hack Week INIT 2023 🔗

• Did 6 challenges
• Created random number generator in C.
• Made a leap year program in Python.
• and much more....

Software used

• Jupyter Notebook
• Python 3.10.2
• Numpy 1.22.4
• pandas 1.4.2
• Matplotlib 3.5.2
• Seaborn 0.11.2
• scikit-learn 1.1.1
• XGBoost 1.6.1
• HTML5
• CSS3
• C

My Notebooks

• Titanic_survival_competition_8.ipynb
• Titanic_survival_competition_9.ipynb
• Titanic_survival_competition_10.ipynb
• MLH - Global Hack Week INIT 2023 hackathon
• • 2022-Goal-sticker
• • Bob Ross MS PAINT
• • Code in Python
• • A project that uses Dataset
• • Show off Github Activity
• • Random Number Generator

Conclusion:

Today I did titanic survival compeition & scored much better by creating new features and participated in Global Hack Week hackathon & completed 6 challenges.