ML Handbook

Table of Contents

Sr. No.	Topic	Summary	Status	Author
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