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7 Must-know Techniques for Encoding Categorical Features
...summarized in a single frame.
 • 
Avi Chawla
Logistic Regression Can NEVER Perfectly Model Well-separated Classes
But isn't well-separated data easiest to separate?
 • 
Avi Chawla
2
Are You Misinterpreting the Purpose of Feature Scaling and Standardization?
Understanding scaling and standardization from the perspective of skewness.
 • 
Avi Chawla
2
A Unique Perspective on Understanding the True Purpose of Hidden Layers in a Neural Network
Intuitive guide to handling non-linearity with neural networks.
 • 
Avi Chawla
2
Feature Discretization: An Underappreciated Technique for Model Improvement
Understanding the rationale behind a powerful yet overlooked technique in machine learning.
 • 
Avi Chawla
2
November 2023
What Makes the Join() Method Blazingly Faster Than Iteration?
A reminder to always prefer specific methods over a generalized approach.
 • 
Avi Chawla
1
An Underrated Technique to Visually Assess Linear Regression Performance
Assumption turned into performance validation.
 • 
Avi Chawla
2
Meet DBSCAN++: The Faster and Scalable Alternative to DBSCAN
Addressing major limitations of the most popular density-based clustering algorithm — DBSCAN.
 • 
Avi Chawla
4
Sourcery: The AI Pair Programmer That Every Python Programmer Must Have
Build reliable, documented and tested projects with Sourcery.
 • 
Avi Chawla
A Visual and Intuitive Guide to What Makes ReLU a Non-linear Activation Function
An intuitive guide to ReLU that you always wanted to read.
 • 
Avi Chawla
2
Effortlessly Scale tSNE to Millions of Data Points With openTSNE
The most optimized CPU implementation of tSNE.
 • 
Avi Chawla
2
This GPU Accelerated tSNE Can Run Upto 700x Faster Than Sklearn
Addressing the limitations of Sklearn
 • 
Avi Chawla
5
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