Master your BCSL606 ML Lab Programs with code and datasets.
A comprehensive resource designed for 3rd Year, 6th Semester VTU Computer Science Engineering students. Access Python code, downloadable datasets, and full visual outputs.
Featured experiment
PCA: 4D to 2D Iris Projection
See how dimensionality reduction reveals separable species clusters.
Datasets
9+
Real and synthetic datasets
Algorithms
12
From Find-S to K-means
Outputs
30+
Charts, plots, and rule exports
Categories
Core ML themes
Track 1
Exploratory Analysis
Track 2
Dimensionality Reduction
Track 3
Concept Learning
Track 4
Semi-Supervised Learning
Track 5
Regression
Track 6
Classification
Track 7
Clustering
Featured experiments
Visual deep dives
EXP1: Data Exploration + Outlier Scan
Histograms, box plots, and IQR-based outlier detection for California Housing features.
EXP2: Correlation Mapping
Correlation heatmap and pair plot to reveal feature relationships.
EXP3: PCA Dimensionality Reduction
Reduce Iris dataset from 4D to 2D and visualize class separation.
Other Resources
More VTU 22 Scheme Lab Programs
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React Lab
BCSL504
Web Technology Lab
BCSL456D
Technical Writing (LaTeX)
ADA Lab
Analysis & Design of Algorithms
Ready to explore?
Start with the full experiment gallery.
Browse by category, follow the learning path, or dive into code and results.