Final project based on text classification by emotions using machine learning models and BERT.
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Updated
Apr 11, 2023 - Jupyter Notebook
Final project based on text classification by emotions using machine learning models and BERT.
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This project focuses on building a fraud detection model for credit card transactions using a dataset containing transactions made by European cardholders in September 2013. We are working with a highly unbalanced dataset and the challenge lies in effectively detecting fraudulent transactions while minimizing false positives.
Klasifikasi Biner dan Multikelas untuk dataset penjualan pada sebuah supermarket
A sentiment analysis project using linear support vector machine with stochastic gradient descent method. Built to analyze whether the tweet sentiment are happy or sad.
Data Project
Here you can explore different projects around Machine Learning Algorithms, Enjoy
A financial institution wants to accurately predict the probability of loanee/borrower defaulting on a vehicle loan in the first EMI on the due date.
implementation of basic ML algorithms
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 150.
Supervised and unsupervised algorthimn analysis on APS Failure at Scania Trucks Dataset
Fake reviews Detection using SGD Classifier
This project develops a machine learning model to classify individuals as healthy, having rheumatoid arthritis (RA), or systemic lupus erythematosus (SLE) using RNA-Seq gene expression data. The project also identifies significant genes as potential biomarkers, leveraging SGDClassifier and XGBoost models.
This project performs analysis and experimentation with classifiers in Python using the MNIST dataset, which consists of images of handwritten digits.
The implications of hate speech have received considerable attention from the common public and society as a whole. There has been a rising concern over the effects of hate speech and offensive language. However, much of this attention is focused on the critical presentation and evaluation of arguments in favor of and against the ban on hate spe…
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