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Intuitive Guides

Building Multi-task Learning Models
A practical guide in PyTorch.
 • 
Avi Chawla
Where Did the GPU Memory Go?
Estimating memory consumption of GPT-2.
 • 
Avi Chawla
Transfer Learning, Fine-tuning, Multitask Learning and Federated Learning
Four critical model training paradigms that you MUST know for real-world ML modelling.
 • 
Avi Chawla
1
Probability vs. Likelihood
Here's the key difference.
 • 
Avi Chawla
3
11 Types of Variables in a Dataset
Beyond features, targets, etc.
 • 
Avi Chawla
3
The True Definition of a Tuple's Immutability
A common misconception.
 • 
Avi Chawla
How to Actually Use Train, Validation and Test Set
Explained with an intuitive analogy.
 • 
Avi Chawla
A Simple Technique to Understand TP, TN, FP and FN
An intuitive guide to binary classification prediction labeling.
 • 
Avi Chawla
4
1:44
Regularize Neural Networks Using Label Smoothing
Make your model less overconfident.
 • 
Avi Chawla
11 Ways to Determine Data Normality
A guide to plotting, statistical and distance methods.
 • 
Avi Chawla
Most Important Plots in Data Science
...in a single frame.
 • 
Avi Chawla
How are QQ Plots Created?
Drawing a QQ plot from scratch.
 • 
Avi Chawla
8
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