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In this Notebook, I analyze the following five semiconductor stocks: HD, INTC, AMD, MU, NVDA, and TSM. Then, I choose the stock with the least correlation to JNJ in order to diversify a portfolio. The data was generated using the GOOGLEFINANCE historical market data script.

  • Updated Mar 24, 2022
  • Jupyter Notebook

In this project I created a notebook that contains data preparation, analysis, and visualizations for all the time series data that a mock company would need to understand including: Visual depictions of seasonality (as measured by Google Search traffic) that are of interest to the company. An evaluation of how the company stock price correlates…

  • Updated Jul 9, 2022

The repository contains various python jupyter notebooks of predicting different medical diseases from various open source datasets.The following medical diseases predicted are cancer,,diabeties,kidney diseases,heart disease,liver diseases,spine disease using variou machine learning classification algorithms like KNN,Logistic Regression,Support …

  • Updated Dec 25, 2020
  • Jupyter Notebook

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