Showing posts with label AI. Show all posts
Showing posts with label AI. Show all posts
Tuesday, February 17, 2026

Split before data pre-processing or after?

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In machine learning workflows, the standard practice is to split datasets into training and testing subsets before applying most preprocessi...

Ruminating on target leakage in ML models

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Target leakage is a type of data leakage where training data includes info directly tied to the outcome (target variable), but that info wou...
Friday, July 25, 2025

Ruminating on FastAPI’s Speed and how to scale it with multiple Uvicorn workers

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Python’s Global Interpreter Lock (GIL) often raises questions about concurrency and performance, especially for web frameworks like FastAPI....
Friday, July 04, 2025

Ruminating on Continued Pre-Training and Fine-Tuning of LLMs

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In my previous blogpost , we discussed about the differences between RAG and Fine-Tuning. Besides fine-tuning, there is another technique ca...
Friday, March 28, 2025

Ruminating on AI Security

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Artificial intelligence has evolved from a distant vision into a transformative force reshaping industries and daily life. Yet, alongside it...
Sunday, February 23, 2025

Crafting an AI strategy for the enterprise

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AI has emerged as a pivotal force for enterprise transformation, offering avenues to reduce operational costs, enhance service delivery, imp...
Tuesday, January 21, 2025

Ruminating on Standardizing Data

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In the realm of statistics, we frequently face datasets of varied sizes and units. This might make it difficult to compare variables or use ...
Wednesday, September 07, 2022

Continuous, Discreet and Categorical variables

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The following websites gives an excellent overview for beginners of the 3 different types of variables that we encounter in feature engineer...
Monday, August 29, 2022

mAP (mean Average Precision) and IoU (Intersection over Union) for Object Detection

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mAP (mean Average Precision) is a common metric used for evaluating the accuracy of object detection models. The mAP computes a score by com...
Sunday, March 27, 2022

Difference between Epoch, Batch and Iterations

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In neural nets, we have to specify the number of epochs while we train the model.  One Epoch is defined as the complete forward & backwa...
Saturday, March 26, 2022

Ruminating on Convolutional Neural Networks

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Convolutional Neural Nets (CNNs) have made Computer Vision a reality. But to understand CNNs, we need to get basics right - What exactly is ...
Friday, March 25, 2022

Ruminating on Activation Function

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 Activation functions play an important role in neural nets. An activation function transforms the weighted sum of the input into an output ...

Ruminating on Gradient Descent

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Gradient Descent is the most popular optimization algorithm used to train machine learning models - by minimizing the cost function. In deep...

Ruminating on 'Fitting the line to data'

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 In linear regression, we need to find the best fit line over a set of points (data). StatQuest has an excellent video explaining how we fit...
Wednesday, March 23, 2022

Ruminating on CUDA and TPU

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  CUDA  is a parallel computing platform (or a programming model - available as an API) that was developed by Nvidia to enable developers le...
Tuesday, March 22, 2022

Understanding what is a Tensor?

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Found this excellent video on YouTube by Prof. Daniel Fleisch that explains tensors in a very simple and engaging way -  https://youtu.be/f5...
Tuesday, March 08, 2022

Ruminating on the Turing Test

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 The Turing Test was made famous by Alan Turing in the year 1950. The Turing Test essentially tests a computer's ability to communicate ...
Sunday, March 06, 2022

Ruminating on n-gram models

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N-gram is a fundamental concept in NLP and is used in many language models. In simple terms, N-gram is nothing but a sequence on N words - e...

Ruminating on Text Normalization

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Text normalization is the process of converting text to a standard form before we use them for training AI NLP models. The following techniq...
Tuesday, February 22, 2022

Ruminating on Fourier Transformation

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 In my AI learning journey, I had to refresh my understanding of fourier transformation. The following video on YouTube is hands-down the be...