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adaboostclassifier

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The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidate…

  • Updated Jan 20, 2022
  • Jupyter Notebook

Classification Project for SDAIA T5 Data Science Bootcamp. This project will choose the best classification model to predict whether a loan is a short-term loan or a long-term loan, based on some features.

  • Updated Dec 10, 2021
  • Jupyter Notebook

Predict the winning probability of white player in a chess game on the basis of first move of white player and first move of black player. In the dataset all the set of moves are given but I choose to predict the white winner the first move

  • Updated Sep 6, 2022
  • Jupyter Notebook

Diabetes is a medical disorder that affects how the body uses food for energy. When blood sugar levels rise, the pancreas releases insulin. If diabetes is not managed, blood sugar levels can rise, increasing the risk of heart attack and stroke. We used Python machine learning to forecast diabetes.

  • Updated Jun 27, 2023
  • Jupyter Notebook

In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.

  • Updated Dec 25, 2023
  • Jupyter Notebook

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