Binary Classification Model

This application creates a model that predicts whether applicants will be successful if funded by the Company. This model will be built using machine learning and neural networks. The Company provided a dataset that contains more than 34,000 organizations that have received funding from the Company over the years.

Steps:

1- Prepare the data for use on a neural network model.

2- Compile and evaluate a binary classification model using a neural network.

3- Optimize the neural network model. 

4- Models comparison and Results

Tecnologies required and installation guide:

TensorFlow

pip install --upgrade tensorflow

- To verify the installation:
``` python -c "import tensorflow as tf;print(tf.__version__)"```

Keras

python -c "import tensorflow as tf;print(tf.keras.__version__)"

Instructions

Use the GC_venture_funding_with_deep_learning.ipynb notebook to create the binary classifier model.

Contributors

Jaime Aranda

License