
Unsupervised Learning Model
Using PCA techiniquea to reduce larger number of componets while retaining essencial information.
The objective is to explore data, reduce the number of features by using dimensionality reduction techniques like PCA and t-SNE, and extract meaningful insights.
Explore 5 questions that will give insights on recent inovations, product development and sustainability practices in the Unied States, Canada and Europe.
A project that tackes five of the most relevant questions to ask a bike company that cathors to an international market.
Using PCA techiniquea to reduce larger number of componets while retaining essencial information.
historical data 1968-2018.
Creating personal ways to reach customers based on preference.
Kitchen supply store.
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