AI-Machine-Learning Index
This folder contains AI-Machine-Learning-related posts.
| # | Blog Link | Date | Excerpt | Tags |
|---|---|---|---|---|
| 1 | Machine Learning | Thu Feb 19 2026 | Overview of AI infrastructure fundamentals including NVIDIA GPU architecture, training vs inference workloads, data center design, networking, storage, virtualization, and AI operations best practices. | NVIDIA, AI Infrastructure, AI Operations, GPU Computing, Data Center, CUDA, AI Training, AI Inference, Networking, Storage, Virtualization, MLOps |
| 2 | Machine Learning: Introduction and Core Algorithms | Thu Feb 19 2026 | Beginner-friendly introduction to machine learning, covering key concepts, model types, supervised and unsupervised learning, and essential algorithms such as linear regression, logistic regression, decision trees, and clustering. | Machine Learning, AI, Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, Algorithms, Data Science |
| 3 | Linear Regression: Concepts and Implementation | Thu Feb 19 2026 | Clear explanation of linear regression, including assumptions, cost function, gradient descent, evaluation metrics, and practical implementation for predictive modeling. | Machine Learning, Linear Regression, Supervised Learning, Regression, Statistics, Model Evaluation, Gradient Descent, Data Science |
| 4 | Multivariate Linear Regression: Concepts and Implementation | Thu Feb 19 2026 | Comprehensive guide to multivariate linear regression, covering multiple input features, model formulation, assumptions, cost function, gradient descent optimization, and evaluation techniques. | Machine Learning, Linear Regression, Multivariate Regression, Supervised Learning, Regression, Feature Engineering, Gradient Descent, Data Science |
| 5 | Normal Equation in Linear Regression | Thu Feb 19 2026 | Detailed explanation of the Normal Equation for linear regression, including matrix formulation, closed-form solution, comparison with gradient descent, and practical considerations for implementation. | Machine Learning, Linear Regression, Normal Equation, Linear Algebra, Supervised Learning, Regression, Matrix Operations, Data Science |