Latest News

My recent articles on Machine Learning, Deep Learning, and AI are closely connected.
Enjoy! I have some valuable insights to share.

Artificial Intelligence, Data Science, News

The Evolving Landscape of AI: Understanding Different AI Paradigms and Their Applications

clustering and segmentation are techniques used in data analysis to group data points based on similarities, but they are applied in different contexts and have distinct goals.

Clustering, Data Science, News, Segmentation

Clustering vs. Segmentation

clustering and segmentation are techniques used in data analysis to group data points based on similarities, but they are applied in different contexts and have distinct goals.

Data Science, GAN, Gen AI, Generative Adversarial Networks, Machine Learning, News, SMOTE, Synthetic Minority Oversampling Technique

SMOTE and GAN: Similarities, Differences, and Applications

What is SMOTE and GAN - Similarities and differences in generating synthetic data from non-linear and intricate datasets, and Applications in healthcare.

CDSS, Data Science, EHR, News

What are the differences between CDSS and EHR system?

CDSS (Clinical Decision Support System) and EHR (Electronic Health Record) systems are related but serve distinct purposes within healthcare settings

Risk Factors / Feature Importances on Google Colab

Data Science, Gen AI, Machine Learning, News

Generative AI refers to a class of AI models that can generate new, synthetic data resembling the data they were trained on. Unlike traditional AI models that are primarily focused on classification or prediction, generative models create new data, such as images, text, or even tabular data

Data Analysis, Data Science, Machine Learning, News

Latest News

The Evolving Landscape of AI: Understanding Different AI Paradigms and Their Applications

Clustering vs. Segmentation

SMOTE and GAN: Similarities, Differences, and Applications

What are the differences between CDSS and EHR system?

A Brief of Generative AI

Google Colab vs. Jupyter vs. Visual Studio Code

How do you evaluate the performance of a machine learning model?

What is regularization and why it is important?

How do you handle missing data?