Data Science and Machine Learning Portfolio

Repository containing portfolio of data science projects completed for academic, self learning, and professional purposes. Presented in the form of Jupyter Notebooks.

Tools

• Python: NumPy, Pandas, Seaborn, Matplotlib
• Machine Learning: scikit-learn, TensorFlow, keras

Contents

• Machine Learning

  • Convolution Neural Network - Digit Recognizer: Convolutional Neural Network that learns to recognize sequences of digits using data generated by concatenating images from MNIST (Recognizes a digit based on an image).
  • K-Nearest Neighbors - Social Network Ads Dataset: Using K-NN on customers that bought a SUV from a social network ad.
  • Monte Carlo Model - Cryptocurrency: Using a probabilistic model on cryptocurrency to find an approximate solution to a numerical problem that would be difficult to solve by other methods.
  • Machine Learning Regression - Financial Market: Importing from quandl (financial and economical data) to create a simple regression.

• Data Analysis and Visualization (Python Programming)

  • Cryptocurrency Market Analysis: Based off my stock market analysis of tech stocks. Change in price over time, daily returns, and behaviour prediction.
  • Stock Market Analysis of Tech Stocks: Analysis of technology stocks including change in price over time, daily returns, and stock behaviour prediction.
  • Exploratory Data Analysis - Titanic Passenger Information: Simple analysis of passengers on board the Titanic answering common questions with visualizations.
  • Exploratory Data Analysis - House Prices: Simple analysis of house prices including quick visualizations with correlation plots and heat maps.
  • Simple Linear Regression: Small playground to summarize and study relationships between two continuous variables from a randomized dataset.

• Minor Projects

  • Personal Notes on Natural Language Processing Toolkit
  • Intro to BigQuery
  • Breast Cancer Analysis

If you enjoyed what you saw, want to have a chat with me about the portfolio, work opportunities, or collaboration, feel free to contact me on: - LinkedIn - Twitter