Benchmarking Project · Python
Marketing-AI-Benchmart
Thesis of Nathan Hazel
What it is
This repository benchmarks multiple machine learning models (logistic regression, SVM, CNN, LSTM, and BERT) for sentiment analysis on a YouTube comments dataset. It includes data preprocessing, model training and evaluation, word analysis per sentiment class, and a comparison of the models' performance.
Merit describes the code at this commit. Later pushes count once the owner rescans. How merit is scored
Where it counts
- Machine Learning90%
- NLP & LLMs70%
- Data Science30%
How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.
Around it on the Machine Learning board
Whole board- 104MLForgeTutorial / Demo · Jupyter Notebook40.9ImplementationVraj PatelMachine Learning
- 105Pix2PixTutorial / Demo · Jupyter Notebook40.5ImplementationSuceveanu Mircea Dan SanduMachine Learning
- 106Marketing-AI-BenchmartBenchmarking Project · Python39.9ImplementationDaffaMachine Learning
- 107AI_for_fun_i_guessTutorial / Demo · Python39.4Implementationvlad andreiMachine Learning
- 108el-relatorML Application · Astro39.1ImplementationMario GutierrezMachine Learning
