🛍️ Analyze E-commerce sales data and build predictive models to uncover customer behavior and purchasing trends using Python and advanced visualization techniques.

🎬 Analyze movie reviews using LSTM for accurate sentiment classification, helping you understand viewer opinions with a balanced dataset.

📊 Analyze Airbnb reviews using AI/ML techniques to classify sentiment and enhance your understanding of user feedback with Python and Jupyter Notebooks.

🎬 Analyze IMDb movie reviews for sentiment using classical and deep learning models, uncovering insights through a comprehensive data science workflow.

🔍 Analyze IMDB movie reviews using LSTM for binary sentiment classification with high accuracy and custom prediction capabilities.

learning how to code.

🧐 This project analyzes Amazon Fine Food Reviews to investigate whether negative reviews are more emotionally intense and lexically repetitive than positive ones. Using R, we apply sentiment analysis and lexical diversity metrics to uncover patterns in consumer review language.

# BERT Mental Health Bot

ADR is a software that identifies and highlights agreements and disagreements in discussion forum messages as a response to the original post.

MER is a software that identifies and highlights manipulative communication in text from human conversations and AI-generated responses. MER benchmarks language models for manipulative expressions, fostering development of transparency and safety in AI. It also supports manipulation victims by detecting manipulative patterns in human communication.

Aspect Sentiment Triplet Extraction Annotations for the MuSe-Car Dataset

This project is a 3-class sentiment analysis app using Hugging Face Transformers and Gradio. It classifies text as Positive, Neutral, or Negative and shows the model’s confidence percentage. The app runs on both Windows and Ubuntu and is easy to set up using a virtual environment.

Sentiment analysis in Elixir.

Readability & Sentiment & Diffusion

Regulations.gov Comment Sentiment Analysis Scraper

Ein Machine-Learning-Projekt, in dem ich Tweets mit NLP-Techniken bereinigt, vektorisiert und mit verschiedenen Modellen klassifiziert habe. Verglichen wurden LogReg, Random Forest und MLP, inklusive Validierung und Hyperparameter-Tuning.

A fully local chat storage app with easy management, emotion classification, and vector memory search

Classifies and detects text entered into major labels (emotion , violence, hate ) and minor labels ( happy , sad, physical_violence, hate_speech etc)

Web integration of distilBert and llama for comments sentiment classification and overall summary.