Docker
What is Docker and why it is used?
Posts by Collection (grid view)
CloudComputing
AI Infrastructure in 2026: What Actually Runs Under the Model
Behind every AI product is a stack of GPUs, schedulers, and cost controls — here’s what running ML workloads in the cloud actually involves.
Cloudy Adventures
Discover the Magic of Cloud Computing!
The ELK Stack: Elasticsearch, Logstash, and Kibana Explained
How three open-source tools combine into one pipeline that turns scattered logs into searchable, visualized data.
Graylog: A Lighter-Weight Alternative to ELK
Graylog centralizes and searches logs like ELK does, but with a smaller operational footprint — here’s when that trade-off makes sense.
Kubernetes: Orchestrating Containers at Scale
Kubernetes turns a pile of containers into a self-healing, auto-scaling system — here’s how pods, deployments, and services actually fit together.
ComputerVision
Know About Computer Vision
Everything You Ever Wanted To Know About Computer Vision.
FACE DETECTION Using OpenCV
Learn how to develop a face identification system Using Haar cascade classifier in PYTHON using OpenCV
FACE DETECTION Using Haar cascade in C.V.
FACE DETECTION Using Haar cascade classifier in PYTHON using OpenCV
Modern OCR Pipelines: From Tesseract to Layout-Aware Document AI
Why classic OCR struggles with real-world documents, and how deep-learning-based pipelines read text, tables, and forms in context.
Segment Anything Model (SAM): Segmentation Without Fixed Classes
How SAM lets you segment any object in an image using a point, a box, or a prompt — no retraining, no predefined class list.
Vision-Language Models: Teaching AI to See and Talk
How models like GPT-4o, Gemini, and LLaVA fuse a vision encoder with a language model so they can describe, read, and reason about images.
YOLO: Real-Time Object Detection Explained
How YOLO looks at an image once and tells you what’s in it and where, fast enough to run on live video.
DeepLearning
Unleashing the Magic of Deep Learning
Chronicles of Deep Learning.
Introduction deep learning
why we need to know about Deep Learning.
LoRA: Fine-tuning Giant Models Without Retraining Them
Why updating billions of frozen weights is wasteful, and how a couple of small low-rank matrices can do the job instead.
Mixture-of-Experts (MoE): Huge Models, Cheap Inference
How routing each input to only a few ‘expert’ sub-networks lets models grow to trillions of parameters without a proportional compute bill.
State Space Models and Mamba: Beyond Quadratic Attention
Why attention gets expensive as sequences grow, and how Mamba borrows ideas from control theory to process long sequences in linear time.
Vision Transformers (ViT): Attention Instead of Convolutions
How the transformer architecture that took over NLP learned to see images, one patch at a time.
Flutter
Configuring & Installing VS code for Flutter and Dart
Guide to install flutter
Flutter Web and WebAssembly: Faster Apps in the Browser
How Flutter runs inside a browser tab at all, and why compiling to WebAssembly instead of JavaScript makes it noticeably faster.
GetX: State Management, DI, and Routing in One Package
GetX bundles reactive state management, dependency injection, and BuildContext-free navigation into a single lightweight library.
Impeller: Flutter’s Modern Rendering Engine Explained
Why Flutter rebuilt its rendering pipeline from scratch, and how Impeller kills the shader-compilation jank that plagued Skia.
Riverpod: Modern State Management for Flutter
A compile-safe, testable way to share and rebuild state in Flutter that fixes the pain points of setState and Provider.
MachineLearning
Essentials of the Machine Learning
Essentials of the Machine Learning algorithm in Python
What is Exploratory Data Analysis?
Exploratory Data Analysis refers to the critical process of performing initial investigations on data.
Step by Step Guide to E.D.A.
An Extensive Step by Step Guide to Exploratory Data Analysis
Under-Construction
Under-Construction
Agentic AI: What Actually Makes a System an ‘Agent’
Planning, tool use, memory, and autonomous multi-step execution are what separate an agentic AI system from a plain chatbot — here’s how it actually works.
AutoML: Automating the Machine Learning Pipeline
AutoML automates feature engineering, model selection, and hyperparameter tuning — but knowing when to trust it (and when not to) is the real skill.
MLOps with MLflow: Tracking, Packaging, and Deploying Models Properly
MLOps turns messy notebook experiments into reproducible, deployable, monitored systems — and MLflow is one of the most popular open-source tools for doing it.
Vector Databases & RAG: Giving LLMs a Memory They Can Trust
How embeddings, vector search, and Retrieval-Augmented Generation combine to ground LLM answers in real data and cut down hallucination.
React
Getting Started with React
A beginner-friendly introduction to React: what it is, why it exists, and how to build your first component.
Next.js App Router: File-Based Routing Meets Server Components
A practical guide to the Next.js App Router — the app/ directory, nested layouts, and how it’s built on top of React Server Components.
React Server Components: Rendering React on the Server
Learn how React Server Components move rendering work off the client, shrink your JavaScript bundle, and change how you think about data fetching.
TanStack Query: Server-State Management for React
Why fetching data with useState and useEffect gets messy fast, and how TanStack Query’s useQuery hook handles caching, refetching, and loading state for you.
Zustand: Minimal Global State Management for React
How Zustand gives React apps simple global state without Redux’s boilerplate, and when to choose it over Context or Redux.
WebDevelopment
Under-Construction
Under-Construction
AI Coding Agents in Web Development: Beyond Autocomplete
How agentic coding tools differ from autocomplete, what a typical agent workflow looks like, and how to review AI-generated code responsibly.
Core Web Vitals Explained: LCP, INP, and CLS
What Google’s Core Web Vitals actually measure, why they affect both SEO and real user experience, and concrete steps to improve each one.
Edge Functions: Running Your Backend Logic Closer to the User
Learn what edge functions actually are, why running code near the user beats a single centralized server region, and how to write one.
WebAssembly (Wasm) for the Web: Running More Than Just JavaScript in the Browser
A practical introduction to WebAssembly — what it is, why it lets languages like C++, Rust, and Dart run near-natively in the browser, and where it’s actuall...