Projects

This page contains information about some of the programming projects on which I have worked, along with samples of code that I have written for these projects.

Contents

• Course Development
• Kaggle Projects
• Other Projects

Course Development

Many of these courses I have developed in recent years have involved programming. The notes I have developed for these courses provide examples of code that I have written. Some notable courses are mentioned below.

• Big Data Analytics - This course covers the use of Apache Spark for performing distributed data analysis. The course emphasizes the use of PySpark to develop applications within a Databricks environment. Specific topics covered in the course include RDDs, Spark DataFrames, Spark SQL, Machine Learning, and Structured Streaming.

• Python for Data Science - This course includes an introduction to Python programming as well as applications of Python in scientific computing, statistics, machine learning, data analysis, and data visualization. Specific packages covered include NumPy, Pandas, Matplotlib, and Scikit-Learn.

• Predictive Modeling - This is a course in statistical learning. It covers the theory of many machine learning algorithms as well using R to apply these algorithms and analyze the results.

• Machine Learning - This is an introductory course in machine learning. The topics covered include using data preparation, classification, regression, validation, and hyperparameter tuning. These notes were developed some time ago and are in desperate need of an update.

• Deep Learning - This is an introductory course in deep learning. Topics covered include using neural networks for classification and regression, CNNs for image classification, RNNs for NLP tasks, and data augmentation. These notes were developed some time ago and are in desperate need of an update.

Kaggle Projects

In this section, I have listed several of the Kaggle competitions on which I have worked. Over time, I will be adding short descriptions of the competitions as well as samples of my work on these competitions.

• Histopathologic Cancer Detection

• G2Net Gravitation Wave Detection

• Freesound General-Purpose Audio Tagging

• IEEE Fraud Detection

• Reducing Commercial Aviation Fatalities

• Forest Cover Type Prediction

• Aerial Cactus Identification

• Cassava Leaf Classification

• CIFAR-10 Object Recognition

• Facial Expression Recognition Challenge

• Home Credit Default Risk

• Quick, Draw! Doodle Recognition Challenge

• What’s Cooking

Other Projects

• Artificial Intelligence Projects To be added.
• Reinforcement Learning Projects To be added.