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Gold-Price-forecasting In a personal endevaour to learn about time series analysis and forecasting, I decided to reserach and explore various quantitative forecasting methods.This notebook documents contains the methods that can be applied to forecast gold price and model deployment using streamlit, along with a detailed explaination of the diff…
This project classifies SMS messages into spam or ham using NLP techniques. It includes data preprocessing, feature extraction with TF-IDF, and classification using models like Naive Bayes, Logistic Regression, and SVM. The notebook also compares model performance using evaluation metrics, providing insights into effective SMS spam detection.
In this notebook we analyze and classify news articles using machine learning techniques, including Logistic Regression, Naive Bayes, Support Vector Machines, and Random Forests. Explore text vectorization and NLP for accurate news categorization.
Project made in Jupyter Notebook with Kaggle Credit Card Fraud Detection Dataset 2023, which aims at selection of best supervised machine learning model for capturing credit card frauds.
A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks
This repository contains a Jupyter notebook implementing the Multinomial Naive Bayes algorithm from scratch for an email classification task of SPAM or HAM. The notebook also includes a comparison of the results obtained with the scikit-learn implementation of Multinomial Naive Bayes.
The repository contains several Jupyter notebooks, each of which covers a different machine learning project, such as sentiment analysis, image classification, and customer segmentation. You also have code examples and datasets included to help users understand and implement the projects themselves.