Data-Science-Projects

Data Science Portfolio for Kevin Thomas. Contains personal and academic projects, presented in the form of Jupyter Notebooks and python scripts. Also includes certificates earned for completing MOOCs.

Contents

Online Courses

• Machine Learning Engineer Nanodegree (Udacity)
  • Software Engineering Practices
    • Files that cover the basics of Object Oriented Programming in Python.
  • Distributions Package
    • A Python package that creates Gaussian and Binomial distributions.
  • Population Segmentation
    • Jupyter Notebook, created in Amazon Sagemaker that performs PCA and K-Means clustering on US Census data.
    • Leveraged Amazon Sagemaker and Amazon S3 to visualize data, and train and deploy models.
  • Credit Card Fraud Detection
• Machine Learning A-Z (Udemy)
  • Supervised Methods
    • Classification
      • Decision Tree Classification
      • Random Forest Classification
      • Naive Bayes
      • Logistic Regression
      • Support Vector Machine (SVM)
      • Kernel SVM
      • K-Nearest Neighbors
    • Regression
      • Simple Linear Regression
      • Support Vector Regression (SVR)
      • Decision Tree Regression
      • Multiple Linear Regression
      • Polynomial Regression
      • Random Forest Regression
  • Unsupervised Methods
    • K-Means Clustering

Mini Projects

• Shark Data Analysis
  Data Cleaning and Exploratory Data Analysis (EDA) performed on Shark Attack data, focussing on Non-USA attacks. Attempted to find hotspots for shark attacks and possible reasons.
• Hacker News Analysis
  Analysis on Hacker News data to find the best time to make a post.