Robust credit risk model that go beyond traditional credit scoring methods in banks
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Updated
Jun 24, 2024 - Jupyter Notebook
Robust credit risk model that go beyond traditional credit scoring methods in banks
Random forest algorithm can be used to analyze hotel booking data and predict booking behavior. This allows hotels to optimize pricing strategies, staffing, and identify potential cancellations for proactive guest communication.
* Basis EDA * Handling Null/Missing Values * Handling Outliers * Handling Skewness * Handling Categorical Features * Data Normalization and Scaling * Feature Engineering
📔 This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explore model optimization techniques such as confusion matrix, precision, recall, Roc curve and F1 score to effectively mitigate default risks.
This is a repository that I have created to showcase skills, share projects and track my progress in Data Analytics / Data Science related topics.
HAM10000 Skin Lesion Classification
Machine learning model
Implementation of Support Vector Machine, and Random Forest Model using sklearn
Machine/Deep Learning Concepts in Time Series Context!
KnowGenius an AI Chatbot who's a General Knowledge Genius!
Data Science: Machine Learning analysis of B2B website Visits and Purchase Patterns
A diverse dataset comprising various car attributes such as mileage, model year, brand, and more, our predictive model employs to accurately forecast the prices of audi car. From data preprocessing to model training and evaluation, our repository provides code implementation, enabling users to understand and replicate our results seamlessly.
reads y_pred and y_true columns from file entities_f1.csv, and then prints output of classification_report function from sklearn.metrics library
Case Study
Machine Learning Model
this repo will include all my work regarding NLP
A classification model to predict those who will likely accept the offer of a new personal loan , by analyzing the previous historical campaign's customer behaviour data.
Dummy TSA Forecast dashboard using statsmodel, sklearn and streamlit
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