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Momentum in ML, Explained Visually and Intuitively!
(a popular ML interview question)
21 hrs ago
•
Avi Chawla
2
A Memory-efficient Technique to Train Large Models
...that even LLMs like GPTs and LLaMAs use.
Oct 14
•
Avi Chawla
1
What is (was?) GIL in Python?
...explained with visuals and code.
Oct 13
•
Avi Chawla
10
6 Graph Feature Engineering Techniques
Must-know for building GNNs.
Jul 31
•
Avi Chawla
5
Prompting vs. RAG vs. Finetuning
Which one is best for you?
Jul 18
•
Avi Chawla
8
2 Techniques to Synchronize ML Models in Multi-GPU Training
...explained visually.
Jul 10
•
Avi Chawla
1
DropBlock vs. Dropout for Regularizing CNNs
Addressing a limitation of Dropout when used in CNNs.
Jul 9
•
Avi Chawla
3
Faster Neighbor Search Using Inverted File Index
...actively used in vector DBs.
Jun 5
•
Avi Chawla
1
5 Chunking Strategies For RAG
...explained in a single frame.
May 29
•
Avi Chawla
8
An Animated Guide to KMeans
In 3Blue1Brown style.
May 25
•
Avi Chawla
5
1:41
How to Actually Use Train, Validation and Test Set
Explained with an intuitive analogy.
Apr 30
•
Avi Chawla
4
RBF Kernel Mathematically Explained
...and why it so powerful.
Apr 29
•
Avi Chawla
1
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