Chipmunk-AI

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  Chipmunk_LOGO

Inspiration

Funny chipmunks that run onto the field during baseball games!

What it does

Chipmunk, an AI-powered baseball prediction model, integrating it with Gemini 2.0 (flash) to provide meaningful baseball-related AI chat for casual viewers.

How we built it

Step 1. Data Analysis & Dataset Preparation: Analyze the dataset and identify missing or erroneous data. Clean the dataset and make it suitable for binary classification, divide the dataset into training and test sets. Step 2. Development: Train the prediction model using supervised learning/binary classification techniques, Evaluate and improve the model's performance, Make the model's outputs compatible with Gemini, Provide Gemini 2.0 Flash Integration and define appropriate roles for Gemini. Step 3. Execute & Presentation: Prepare promotional videos and/or documents related to the project Present the project to the team, addressing their questions and gathering feedback.

Challenges we ran into

Raw data cleaning, preparation for modeling, training and testing process

Accomplishments that we're proud of

Seeing the potential of Chipmunk-AI to transform baseball strategy has been a rewarding experience.

What we learned

We improved our data science skills and discovered new AI tools.

What's next for Chipmunk-AI

Next, we aim to build an interactive platform where baseball enthusiasts can come together, engage, and use AI tools collaboratively.

Built With

• cloudflarepages
• colab
• css3
• dockerhub
• excalidraw
• figma
• flask
• gemini
• github
• golang
• google-translate
• googlecloudplatform
• googlecloudrun
• googleworkspace
• html5
• joblib
• numpy
• pandas
• purejs
• python
• scikit-learn
• vertexai