Bank card fraud detection using machine learning. Web application using Streamlit framework
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Updated
Jun 26, 2024 - Python
Bank card fraud detection using machine learning. Web application using Streamlit framework
Sklearn, logistic regression, Naive Bayes classifier, K-Nearest Neighbors, decision trees
A new method of supervised feature scaling using decision tree
The primary objective of this study is to explore the feasibility of using machine learning algorithms to classify health insurance plans based on their coverage for routine dental services. To achieve this, I used six different classification algorithms: LR, DT, RF, GBT, SVM, FM(Tech: PySpark, SQL, Databricks, Zeppelin books, Hadoop, Spark-Submit)
Complete Tutorial Guide with Code for learning ML
Implementation of decision trees for classification and regression as objects similar to sklearn's.
Email Spam detection using KNN and Decision Trees Models Trained using the Spambase database
Implemented Traditional ML models for Regression and Classification using sklearn.
In This Repository you can find The Explanation and The Implementation of the Most Famous Machine Learning Algorithms
Repository For Codes And Concept Taught in Udemy Course
Classification of mushrooms using decision tree in ID3 implementation
An implementation of Random Forests in the Python programming language (accuracy tested with 100, 300, and 500 trees)
My implementations of Linear Regression, Logistic Regression
Final project for IEE 520 Stat learning for data mining. Highly imbalanced data set. Sampling methods used.
Machine learning algorithms from scratch in python.
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