1 |
Dealing with missing-values |
The notebook explores types of missingness and techniques for imputation. |
Completed |
Alape Aniruddha |
2 |
Comprehensive Study on the Impact of Feature Scaling on Classification Models |
An Introduction to Scaling. |
Completed |
Sherry Thomas |
3 |
Investigation of Standard Scaling Influence |
A deep dive into Standard Scaling. |
Completed |
Sherry Thomas |
4 |
Visualizations for Data Science: An Overview |
A general overview on how data visualization is handled. |
Completed |
Sherry Thomas |
5 |
Comprehensive Data Visualization with Matplotlib and Seaborn |
Code and Implementation of various visualization techniques using Matplotlib and Seaborn. |
Completed |
Sherry Thomas |
6 |
Accuracy |
The notebook discusses accuracy in classification, its issues, calculation, and tuning using sklearn. |
Completed |
Alape Aniruddha |
7 |
F1 Score |
The notebook discusses F1 Score in classification metrics using sklearn. |
Completed |
Alape Aniruddha |
8 |
Recall in Classification Metrics |
The notebook explains recall in binary classification using sklearn metrics. |
Completed |
Alape Aniruddha |
9 |
Precision in Classification Metrics |
The notebook explores precision in classification, its calculation, and application. |
Completed |
Alape Aniruddha |
10 |
Exploring the Significance of ROC AUC in Classification Models |
The notebook explores ROC-AUC in classification, its calculation, and application. |
Completed |
Sherry Thomas |
11 |
Inductive Bias in Decision Trees and K-Nearest Neighbors |
Exploring inductive bias impact on classifiers using synthetic datasets and algorithms. |
Completed |
Vivek Sivaramakrishnan |
12 |
Ordinal Classification |
Ordinal classification explored using logistic regression and alternative encoding methods. |
Completed |
Vivek Sivaramakrishnan |
13 |
EM Algorithm |
The notebook demonstrates the Expectation-Maximization algorithm on a Gaussian Mixture Model. |
Completed |
Vivek Sivaramakrishnan |
14 |
Probabilistic PCA |
The notebook explores Probabilistic PCA through generative modeling and EM algorithm. |
Completed |
Vivek Sivaramakrishnan |
15 |
Predictive Modeling of Patient Status in Primary Biliary Cirrhosis |
A case study, EDA and modeling on a medical dataset. |
Completed |
Sherry Thomas |
16 |
Predicting Bank Customer Churn |
A case study, EDA and modeling on a banking dataset. |
Completed |
Sherry Thomas |
17 |
Agglomerative Clustering |
Hierarchical clustering with agglomerative approach, dendrograms, and linkage methods explored visually. |
Completed |
Vivek Sivaramakrishnan |