This application creates a neural network model that predicts whether applicants will be successful if funded by the venture capital firm Alphabet Soup.
The data for this application is a CSV file containing more than 34,000 organizations that have received funding from Alphabet Soup over the years. The CSV file contains a variety of information about each business, including whether or not it ultimately became successful. The application creates a binary classifier model that will predict whether an applicant will become a successful business. Specifically the application:
- Preprocesses data for a neural network model.
- Uses the model-fit-predict pattern to compile and evaluate a binary classification model.
- Optimizes the model by creating two alternative analyses using different inputs and evaluates the results.
- Clone this repository by opening your terminal and entering the following commands:
git clone https://github.com/jgrichardson/venture_funding_with_deep_learning.git
This application runs as a Jupyter Lab notebook. Open your terminal, navigate to the cloned directory, and type:
jupyter lab
The source code for the application is licensed under the MIT license, which you can find in the LICENSE file in this repo.