Pokemon Analysis

• 

  Analysis of Pokemon Types

Inspiration

As a kid, we guys were very fascinated by pokemon playing cards. Fast forward to 2022, we now know Machine Learning Algorithms, Thus, major reason for our analysis.

What it does

Analyze and Predict Pokemon's Legendary Status.

How we built it

• We used Jupyter Notebook for our platform.
• For analysis and visualization, we used matplotlib and seaborn.
• Logistic Regression and Random Forest Classifier for Prediction.

Challenges we ran into

We were getting low prediction accuracy, so, we used Random forest to increase it.

Accomplishments that we're proud of

We are achieving 95% accuracy on our testing data.

What we learned

We learned many visualization tools and prediction algorithms

What's next for Pokemon Analysis

We though of creating a web-app for our prediction algorithms.

Built With

• jupyter-notebook
• python