Data Science Portfolio

Repository containing portfolio of data science projects completed by me for academic, self learning, and hobby purposes. Presented in the form of iPython Notebooks,

Note: Data used in the projects (accessed under data directory) is for demonstration purposes only.

Contents

• Machine Learning

  • Predicting Pnueomonia: This Deep learning model predicts whether a person is infected with Pneumonia or not with an accuracy of nearly 98 percentage, by taking an image of a chest X-ray as input.

  • Cat vs Dog Classification: Cat and dog classification using CNN Convolutional Neural Network (CNN) is an algorithm taking an image as input then assigning weights and biases to all the aspects of an image and thus differentiates one from the other.

  • Predicting Boston housing price: A model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.

  • Stock Market Prediction: Designing and implementing a Time series forecasting model based on Deep Learning, and different Statistical features, that predict the future stock price.

  • Stock Trend Prediction Using News Sentiment Analysis: his project is about taking non quantifiable data such as financial news articles about a company and predicting its future stock trend with news sentiment classification. Assuming that news articles have impact on stock market, this is an attempt to study relationship between news and stock trend.
  Tools: scikit-learn, Pandas, Seaborn, Matplotlib, Pygame