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Tanayendu Bari

@lagranJoined June 2025

A Database that can think

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Tanayendu Bari's blogs

Dijkstra's Is No Longer the Fastest Pathdijkstras-is-no-longer-the-fastest-path.hashnode.dev1 post Convolutional Neural Networks (CNNs)convolutional-neural-networks-cnns.hashnode.dev1 post What Happens Before Attention?what-happens-before-attention.hashnode.dev1 post Embeddingsembeddings.hashnode.dev1 post Binary Classification using Pytorchbinary-classification-using-pytorch.hashnode.dev1 post

Multi-Class Image Classification with FashionMNIST in PyTorch

Introduction In this tutorial, we’ll walk through building a multi-class image classification model using PyTorch and the FashionMNIST dataset. This task involves identifying 10 categories of clothing such as shirts, trousers, and sneakers. PyTorch ...

Jun 25, 2025 · 10 min readmulti-class-image-classification.hashnode.dev

Binary Classification with PyTorch: A Step-by-Step Guide

Introduction Binary classification is one of the most fundamental tasks in machine learning. Whether you're predicting if an email is spam or not, detecting fraudulent transactions, or diagnosing whether a tumor is malignant or benign — all of these ...

Jun 23, 2025 · 9 min readbinary-classification-using-pytorch.hashnode.dev

Embeddings in NLP: From One-Hot to Transformers

Introduction: What Are Embeddings? In natural language processing (NLP) and deep learning, embeddings refer to a technique used to transform discrete, symbolic data—such as words, characters, or even entire sentences—into continuous, dense vectors in...

Jun 23, 2025 · 9 min readembeddings.hashnode.dev

Understanding the Transformer Input Layer: Tokenization Explained.

Introduction The first layer of a Transformer model is the input layer, and it typically consists of two major components: tokenization and embeddings. Before the model can perform attention, reasoning, or prediction, it must first understand the inp...

Jun 19, 2025 · 26 min readwhat-happens-before-attention.hashnode.dev

From Pixels to Patterns: A Deep Dive into Convolutional Neural Networks (CNNs)

Introduction Convolutional Neural Networks (CNNs) have dramatically transformed the landscape of computer vision, enabling machines to perceive and interpret visual data with unprecedented accuracy and efficiency. Initially developed for tasks like h...

Jun 17, 2025 · 18 min readconvolutional-neural-networks-cnns.hashnode.dev

Tanayendu Bari

About

Available for

Tanayendu Bari's blogs

Multi-Class Image Classification with FashionMNIST in PyTorch

Binary Classification with PyTorch: A Step-by-Step Guide

Embeddings in NLP: From One-Hot to Transformers

Understanding the Transformer Input Layer: Tokenization Explained.

From Pixels to Patterns: A Deep Dive into Convolutional Neural Networks (CNNs)

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Tanayendu Bari

About

Available for

Tanayendu Bari's blogs

Multi-Class Image Classification with FashionMNIST in PyTorch

Binary Classification with PyTorch: A Step-by-Step Guide

Embeddings in NLP: From One-Hot to Transformers

Understanding the Transformer Input Layer: Tokenization Explained.

From Pixels to Patterns: A Deep Dive into Convolutional Neural Networks (CNNs)