Files relevant for my bachelor thesis on different automatic emotion recognition approaches

This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.

Predicting Hepatocellular Carcinoma through Supervised Machine Learning

In today's financial market,news sentiment plays a crucial role in shaping investor behavior and influencing stock prices. By analyzing the sentiment behind stock-related news articles, investors can gain valuable insights to make informed trading decisions.We have performed sentiment analysis of the twitter data based on a whole day to analyse it.

A regression problem side project using scikit-learn to predict housing price in balikpapan

Quantile Regression Forests compatible with scikit-learn.

AI Resume Screening is a tool that uses artificial intelligence to automate the process of resume screening and shortlisting. The tool uses natural language processing and machine learning algorithms to analyze resumes and classify them to the job roles based on the words in their resume.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

₿ Bitcoin 🚀 predictions 🪙

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Using R Markdown for Data Analysis, Machine Learning

Estimación de turbidez en el agua a la entrada de la planta de tratamiento de SAMEEP, utilizando los productos Sentinel-2 MSI L2A y aprendizaje automático.

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

AIML Projects

This project uses the Seaborn 'tips' dataset to demonstrate a machine learning pipeline, including data preprocessing, feature engineering, and model evaluation with RandomForest, DecisionTree, and LogisticRegression classifiers.

Our goal in this project was to develop statistical and machine learning models to replicate the functionality of the traditional Black-Scholes option pricing formula, specifically for valuing European call options.

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

🍊 📊 💡 Orange: Interactive data analysis

Sample for the German article "Anomalie-Erkennung für Echtzeit-Datenströme" by Constantin Gonzalez and Florian Mair published in Big Data Insider.

🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯