cdenq/charity-funding-success-predictor

Deep learning project that predicts whether a charity would be successful after funding from Alphabet Soup. Data contains 34k data points and was analyzed using a hypertuned neural network.

charity-funding-success-predictor

About Charity Funding Predictor

Charity Funding Predictor is a Tensorflow machine learning challenge that predicts whether a charity will be successfully funded. The machine learning models used are a custom neural network, which has been tested between 1-6 layers, each at 1-10 neurons.

Charity data is sourced from Alphabet Soup and is around 34k data points.

Google Colab file can be found here.

Built with

• Python
• Google Colab
• Tensorflow
  • Keras
  • Keras Tuner

Technical Skills

• Data preprocessing for machine learning
• Applying machine learning models on datasets
• Hyperparameter tuning and results analysis

Screenshots