Models included in the course:
- Supervised Learning:
- Model Building and Error Analysis
- Linear Regression
- Gradient Descent
- Logistic Regression
- Deep Neural Network
- k-Nearest Neighbors
- Decision/ Regression Trees
- Ensemble methods
- Unsupervised Learning:
- k-Means Clustering
- Principle Component Analysis
Datasets included in the course:
-
Wheat seed dataset:
- Similar to iris dataset. The data set contains seed information belonging to three different wheat varieties: Kama, Rosa and Canadian, represented by 1, 2 and 3 respectively
- Link:https://www.kaggle.com/datasets/jmcaro/wheat-seedsuci
-
Fashion MNIST dataset:
- It has the same structure as MNIST dataset, with a training set of 60000 samples and a test set of 10000 clothing images. The size of the image is also fixed to 28 × 28. In this way, the preprocessed image data is reduced to the minimum level.
- Link:https://www.kaggle.com/datasets/zalando-research/fashionmnist
-
Anime Recommendations Database:
- The dataset contains the name and type of animation and the ratings of animation by more than 70000 users.
- Link:https://www.kaggle.com/datasets/CooperUnion/anime-recommendations-database
-
Boston Housing dataset:
- The Boston housing dataset consists of 14 features and contains information collected by the U.S. Census Bureau about housing in Boston, Massachusetts.
- Link:https://www.kaggle.com/competitions/boston-housing/overview/description