Code | Krishnatheja Vanka

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JAX for PyTorch Users

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A Verbose, Beginner-Friendly Guide

August 18, 2026·34 min read

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A Beginner’s Guide to Metric Visualization

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From TensorBoard to MLflow

July 27, 2026·21 min read

PyTorch Automatic Mixed Precision (AMP): A Comprehensive Guide

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Automatic Mixed Precision (AMP) is PyTorch’s mechanism for running selected parts of a model in lower-precision floating point formats (float16 or bfloat16)…

July 10, 2026·21 min read

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

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Paper: arXiv:2301.12597 (v3, 15 Jun 2023) Authors: Junnan Li, Dongxu Li, Silvio Savarese, Steven Hoi — Salesforce Research Code:…

July 6, 2026·20 min read

Learning Transferable Visual Models From Natural Language Supervision (CLIP)

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Paper: Learning Transferable Visual Models From Natural Language Supervision Authors: Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh,…

July 6, 2026·39 min read

FlashAttention for Image Models

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Attention is the computational core of nearly every modern image model — Vision Transformers (ViT) for classification and representation learning, Diffusion…

July 2, 2026·21 min read

Targeted Fine-Tuning from Model Mispredictions with Milvus

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This guide walks through the full pipeline for identifying images your model predicts incorrectly, storing and querying them using Milvus as the vector…

June 22, 2026·26 min read

Training a Model with Milvus and PyTorch: A Comprehensive Guide

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This guide covers how to build a full machine learning pipeline that combines PyTorch for model training with Milvus as a vector database — a common…

June 22, 2026·21 min read

A Verbose Guide to LeNet: The Pioneer of Convolutional Neural Networks

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LeNet is the name given to a series of convolutional neural network (CNN) architectures developed primarily by Yann LeCun, along with collaborators Léon…

June 20, 2026·22 min read

AlexNet: A Comprehensive Guide

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AlexNet is a deep convolutional neural network (CNN) that fundamentally changed the landscape of computer vision and machine learning when it was introduced in…

June 15, 2026·24 min read

Training Computer Vision Models and Running Them with ONNX Runtime

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Computer vision is one of the most vibrant areas of applied machine learning. Whether you are building an image classifier, a real-time object detector, a…

May 19, 2026·30 min read

Building Neural Network Architectures Using Only ONNX

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ONNX (Open Neural Network Exchange) is most commonly known as an export target — a format you dump a PyTorch or TensorFlow model into for deployment. But ONNX…

May 19, 2026·34 min read

Milvus for Computer Vision: An In-Depth Guide

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I’ve spent a fair bit of time working on computer vision systems — the kind that start small, manageable, and almost deceptively simple, and then quietly…

May 7, 2026·47 min read

TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment

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Vision-language models (VLMs) have become a cornerstone of modern computer vision and multimodal AI. Systems like CLIP, SigLIP, ALIGN, and their descendants…

April 23, 2026·20 min read

GitHub Actions × MLFlow CI/CD for Computer Vision

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A practitioner’s guide to building reliable, reproducible, and observable CV model pipelines using GitHub Actions and MLFlow.

April 9, 2026·17 min read

MLflow Best Practices for Computer Vision (Deep Learning)

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Operational Excellence in Production Systems

April 9, 2026·8 min read

Grounding DINO Implementation Guide

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Grounding DINO is a state-of-the-art open-set object detection model that combines language understanding with visual detection. It can detect and localize…

December 21, 2025·7 min read

$Mathematics Behind Grounding DINO$

Mathematics Behind Grounding DINO

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Grounding DINO (Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection) is a state-of-the-art open-set object detection model…

December 21, 2025·4 min read

Programming Languages in Computer Vision & Machine Learning

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When I look back at my career so far, it feels like a journey through different languages, each chapter shaping the way I think about solving problems.

September 30, 2025·27 min read

SGLang: Comprehensive Guide to Structured Generation Language

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SGLang (Structured Generation Language) is a revolutionary framework that transforms how developers interact with large language models (LLMs) and…

August 25, 2025·12 min read

Complete Guide to Mamba Transformers: Implementation and Theory

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Mamba is a revolutionary architecture that addresses the quadratic complexity problem of traditional transformers through selective state space models (SSMs).…

August 23, 2025·22 min read

Mamba Transformers: Revolutionizing Sequence Modeling with Selective State Space Models

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Mamba represents a groundbreaking advancement in sequence modeling architecture, emerging as a compelling alternative to the dominant transformer paradigm.…

August 23, 2025·9 min read

Complete Guide to Quantization and Pruning

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Model compression techniques are essential for deploying deep learning models in resource-constrained environments. Two of the most effective approaches are…

August 22, 2025·7 min read

Complete Guide to DINOv3: Self-Supervised Vision Transformers

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DINOv3 represents a breakthrough in computer vision, offering the first truly universal vision backbone that achieves state-of-the-art performance across…

August 22, 2025·10 min read

Vision-Language Models: Bridging Visual and Textual Understanding

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Vision-Language Models (VLMs) represent one of the most exciting frontiers in artificial intelligence, combining computer vision and natural language…

August 2, 2025·8 min read

Fine-tuning Vision-Language Models: A Comprehensive Guide

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Vision-Language Models (VLMs) represent a significant advancement in artificial intelligence, combining computer vision and natural language processing to…

August 2, 2025·24 min read

LoRA for Vision-Language Models: A Comprehensive Guide

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Low-Rank Adaptation (LoRA) has emerged as a revolutionary technique for efficient fine-tuning of large language models, and its application to Vision-Language…

August 2, 2025·39 min read

Complete Guide to Stable Diffusion with ControlNet

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ControlNet is a neural network architecture that allows you to control Stable Diffusion image generation with additional input conditions like edge maps, depth…

July 22, 2025·10 min read

DenseNet: A Code Guide

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DenseNet (Densely Connected Convolutional Networks) represents a paradigm shift in deep learning architecture design, introducing unprecedented connectivity…

July 19, 2025·13 min read

Complete MobileNet Code Guide

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MobileNet is a family of efficient neural network architectures designed specifically for mobile and embedded devices. The key innovation is the use of…

July 19, 2025·23 min read

Complete YOLO Object Detection Code Guide

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YOLO (You Only Look Once) is a state-of-the-art real-time object detection algorithm that revolutionized computer vision by treating object detection as a…

July 12, 2025·9 min read

Neural Architecture Search: Complete Code Guide

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Neural Architecture Search (NAS) is an automated approach to designing neural network architectures. Instead of manually crafting network designs, NAS…

July 11, 2025·21 min read

Optuna for Deep Learning and Neural Architecture Search: A Comprehensive Guide

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Hyperparameter optimization is one of the most critical yet challenging aspects of deep learning. With the exponential growth in model complexity and the vast…

July 11, 2025·11 min read

Complete Guide to Python’s functools Module

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The functools module in Python provides utilities for working with higher-order functions and operations on callable objects. It’s a powerful toolkit for…

July 6, 2025·13 min read

Complete Guide to Python’s itertools Module

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The itertools module is one of Python’s most powerful standard library modules for creating iterators and performing functional programming operations. It…

July 6, 2025·18 min read

Python Multiprocessing and Multithreading: A Comprehensive Guide

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Python provides two primary approaches for concurrent execution: multithreading and multiprocessing. Understanding when and how to use each is crucial for…

July 6, 2025·18 min read

Convolutional Kolmogorov-Arnold Networks: A Deep Dive into Next-Generation Neural Architectures

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Convolutional Kolmogorov-Arnold Networks (CKANs) represent a groundbreaking fusion of classical mathematical theory and modern deep learning architectures. By…

July 5, 2025·8 min read

Kolmogorov-Arnold Networks: Complete Implementation Guide

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Kolmogorov-Arnold Networks (KANs) represent a paradigm shift in neural network architecture, drawing inspiration from the mathematical foundations laid by…

July 2, 2025·10 min read

PyTorch 2.x Compilation Pipeline: From FX to Hardware

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PyTorch 2.x introduced a revolutionary compilation stack that transforms high-level Python code into highly optimized machine code. This guide explores the…

June 30, 2025·11 min read

Matryoshka Transformer: Complete Implementation Guide

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Matryoshka Transformers are a neural architecture that enables flexible computational budgets during inference by allowing early exits at different layers.…

June 28, 2025·7 min read

Attention Mechanisms: Transformers vs CNNs - Complete Code Guide

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Attention mechanisms have revolutionized deep learning by allowing models to focus on relevant parts of input data. While Transformers use self-attention as…

June 27, 2025·10 min read

CUDA Python: Accelerating Python Applications with GPU Computing

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CUDA Python brings the power of NVIDIA’s CUDA platform directly to Python developers, enabling massive parallel computing capabilities without leaving the…

June 22, 2025·6 min read

Python Decorators: A Complete Guide with Useful Examples

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Python decorators are one of the most powerful and elegant features of the language. They allow you to modify or enhance the behavior of functions, methods, or…

June 22, 2025·5 min read

DeepSpeed with PyTorch: Complete Code Guide

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DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. It provides system innovations like ZeRO…

June 21, 2025·8 min read

PyTorch Model Deployment on Edge Devices - Complete Code Guide

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This guide provides a comprehensive approach to deploying PyTorch models on edge devices. Key takeaways:

June 21, 2025·9 min read

Distributed Training with PyTorch - Complete Code Guide

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Distributed training allows you to scale PyTorch models across multiple GPUs and machines, dramatically reducing training time for large models and datasets.…

June 21, 2025·8 min read

Getting Started with Rust: A Complete Guide

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Rust is a systems programming language that focuses on safety, speed, and concurrency. It prevents common programming errors like null pointer dereferences and…

June 14, 2025·6 min read

Hugging Face Accelerate Code Guide

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This comprehensive code guide covers everything you need to know about Hugging Face Accelerate, from basic setup to advanced features like DeepSpeed…

June 3, 2025·6 min read

PyTorch Lightning Fabric Code Guide

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I’ve created a comprehensive code guide for PyTorch Lightning Fabric that covers everything from basic setup to advanced distributed training features

June 3, 2025·7 min read

PyTorch Collate Function Speed-Up Guide

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The collate function in PyTorch is a crucial component for optimizing data loading performance. It determines how individual samples are combined into batches,…

June 1, 2025·7 min read

PyTorch Training and Inference Optimization Guide

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The guide includes practical code examples you can directly use in your projects, along with best practices and common pitfalls to avoid. Each section builds…

June 1, 2025·5 min read

Kubeflow Deep Learning Guide with PyTorch

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Kubeflow is a machine learning toolkit for Kubernetes that makes deployments of ML workflows on Kubernetes simple, portable, and scalable. This guide focuses…

May 31, 2025·9 min read

MLflow for PyTorch - Complete Guide

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MLflow is an open-source platform for managing the machine learning lifecycle, including experimentation, reproducibility, deployment, and model registry. This…

May 30, 2025·5 min read

CLIP Code Guide: Complete Implementation and Usage

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CLIP (Contrastive Language-Image Pre-training) is a neural network architecture developed by OpenAI that learns visual concepts from natural language…

May 29, 2025·9 min read

DINOv2 Student-Teacher Network Training Guide

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This guide provides a complete implementation for training a DINOv2 (DINO version 2) student-teacher network from scratch using PyTorch. DINOv2 is a…

May 28, 2025·8 min read

Student-Teacher Network Training Guide in PyTorch

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Student-teacher networks, also known as knowledge distillation, involve training a smaller “student” model to mimic the behavior of a larger, pre-trained…

May 28, 2025·8 min read

LitServe Code Guide

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LitServe is a high-performance, flexible AI model serving framework designed to deploy machine learning models with minimal code. It provides automatic…

May 27, 2025·8 min read

LitServe with MobileNetV2 - Complete Code Guide

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This guide demonstrates how to deploy a MobileNetV2 image classification model using LitServe for efficient, scalable inference.

May 27, 2025·9 min read

Albumentations vs TorchVision Transforms: Complete Code Guide

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This guide compares two popular image augmentation libraries for PyTorch:

May 27, 2025·5 min read

MobileNetV2 PyTorch Docker Deployment Guide

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This guide walks you through deploying a pre-trained MobileNetV2 model using PyTorch and Docker, creating a REST API for image classification.

May 26, 2025·11 min read

PyTorch to PyTorch Lightning Migration Guide

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PyTorch Lightning is a lightweight wrapper around PyTorch that eliminates boilerplate code while maintaining full control over your models. It provides a…

May 25, 2025·7 min read

Python 3.14: Key Improvements and New Features

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Python 3.14 introduces several significant improvements focused on performance, developer experience, and language capabilities. This guide covers the most…

May 24, 2025·6 min read

DINOv2: Comprehensive Implementation Guide

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DINOv2 is a state-of-the-art self-supervised vision model developed by Meta AI Research that builds upon the original DINO (Self-Distillation with No Labels)…

May 3, 2025·9 min read

Vision Transformer (ViT) Implementation Guide

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Vision Transformers (ViT) represent a significant paradigm shift in computer vision, applying the transformer architecture initially developed for NLP to image…

April 26, 2025·11 min read

Active Learning Influence Selection: A Comprehensive Guide

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Active learning is a machine learning paradigm where the algorithm can interactively query an oracle (typically a human annotator) to label new data points.…

April 19, 2025·20 min read

Python Data Visualization: Matplotlib vs Seaborn vs Altair

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This guide compares three popular Python data visualization libraries: Matplotlib, Seaborn, and Altair (Vega-Altair). Each library has its own strengths,…

April 12, 2025·9 min read

From Pandas to Polars

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As datasets grow in size and complexity, performance and efficiency become critical in data processing. While Pandas has long been the go-to library for data…

April 5, 2025·9 min read

PyTorch Lightning: A Comprehensive Guide

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PyTorch Lightning is a lightweight wrapper for PyTorch that helps organize code and reduce boilerplate while adding powerful features for research and…

March 29, 2025·7 min read