Files relevant for my bachelor thesis on different automatic emotion recognition approaches
-
Updated
May 24, 2024 - Jupyter Notebook
Files relevant for my bachelor thesis on different automatic emotion recognition approaches
Dive into the world of Machine Learning in this immersive lab course, exploring open-source tools and algorithms such as random forest, SVM, linear regression, PCA, K-means, LDA, KNN, decision tree, and more. Engage in real-world ML projects and deploy your models, gaining practical experience in the forefront of AI technology.
Coronavirus disease (COVID-19) pandemic Visualization & Prediction
PrognosisHub is a multiple disease predictor.
This code loads network data, preprocesses it, reduces dimensions with an autoencoder, and trains multiple classifiers (KNN, RF, LR, SVM) for anomaly detection.
Code for Tensorflow Machine Learning Cookbook
Machine Learning project - CMP2024 - Computer Engineering - Cairo University
Statistical Learning Algorithm Implementation.
Prediction of loan status based on training ML models on historical data and predict status, complete with thorough Data Visualization and Exploratory Data analysis
Towards evaluation of fairness in MDD models: Automatic analysis of symptom differences for gender groups in the D-vlog dataset
Implementing SVM's using pandas and sklearn in python
The Operator Splitting QP Solver
An Interactive Dashboard for Predicting Bank Customer Attrition
Sentiment Classification with Bagging and SVM
Explore NLP model evaluation on answer scores and tweet sentiment. Features preprocessing, BoW, TF-IDF, Word2Vec, and models like Linear Regression, Decision Tree, SVM, Logistic Regression, and Random Forest.
Applicazione dei concetti e dei metodi appresi durante il corso di Fondamenti di Scienza dei Dati. Con particolare attenzione all'analisi e alla classificazione del famoso dataset Iris.
A Streamlit webapp that predicts diabetes based on patient data.
Projekt u sklopu predmeta Analiza slika u biomedicini
Add a description, image, and links to the svm topic page so that developers can more easily learn about it.
To associate your repository with the svm topic, visit your repo's landing page and select "manage topics."