DSCI 552: Machine Learning for Data Science (Fall 2022)

Practical applications of machine learning techniques to real-world problems. Uses in data mining and recommendation systems and for building adaptive user interfaces.

Course Description

This is a foundational course with the primary application to data analytics, but is intended to be accessible both to students from technical backgrounds such as computer science, computer engineering, electrical engineering, or mathematics; and to students from less technical backgrounds such as business administration, communication, accounting, various medical specializations including preventative medicine and personalized medicine, genomics, and management information systems. A basic understanding of engineering and/or technology principles is needed, as well as basic programming skills, sufficient mathematical background in probability, statistics, and linear algebra.

Homework

Topic	Programming	Tags	Data
KNN Classification	Jupyter Notebook	EDA Classification KNN	Vertebral Column
Regression	Jupyter Notebook	Linear Regression Multiple Regression KNN Regression Hypothesis Testing	Combined Cycle Power Plant
Time Series Classification Part 1	Jupyter Notebook	Time-domain Features Extraction Bootstrapping	AReM data
Time Series Classification Part 2	Jupyter Notebook	Binary Classification Multiclass Classification Logistic Regression	AReM data
Decision Trees	Jupyter Notebook	Decision Trees Cost-complexity Pruning Ridge regression LASSO Boosting	Acute Inflammations Communities and Crime
Tree-Based Methods	Jupyter Notebook	Random Forest Class Imbalance SMOTE XGBoost	APS Failure at Scania Trucks
Support Vector Machines	Jupyter Notebook	SVM K-Means Clustering Monte-Carlo Simulation	Anuran Calls (MFCCs)

Project: Transfer Learning for Image Classification

In this problem, we are trying to build a classifier that distinguishes images of 20 bird species.

Topic	Programming	Tags	Notes
Image Classification	Jupyter Notebook	TensorFlow Keras OpenCV EfficientNetB0 VGG16	Due to the large size of the dataset, the images are not included in this repository.