You work as a risk management associate at Alphabet Soup, a venture capital firm. Alphabet Soup’s business team receives many funding applications from startups every day. This team has asked you to help them create a model that predicts whether applicants will be successful if funded by Alphabet Soup.
The business team has given you 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. With your knowledge of machine learning and neural networks, you decide to use the features in the provided dataset to create a binary classifier model that will predict whether an applicant will become a successful business.
To predict whether Alphabet Soup funding applicants will be successful, you will create a binary classification model using a deep neural network.
The technologies required for the program to run are as follows:
pandashttps://pandas.pydata.org/
sklearnhttps://scikit-learn.org/stable/
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This challenge consists of three technical deliverables. You will do the following:
* Preprocess data for a neural network model. * Use the model-fit-predict pattern to compile and evaluate a binary classification model. * Optimize the model.
Available at: https://courses.bootcampspot.com/courses/1251/assignments/25275?module_item_id=511758
Scott J. Marler
LinkedIn Profile: https://www.linkedin.com/in/scott-marler-212040b6/