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Hi πŸ‘‹, I'm Md Ali Azad

I possess a deep passion for artificial intelligence, computer vision, natural language processing, machine learning, and deep learning. My enthusiasm has translated into tangible results through various projects, such as the development of a live crack detection system and an interactive trainer chatbot designed for new learners. In addition to my expertise in AI, I am well-versed in web development, further expanding my skill set in crafting innovative solutions.

md-ali-azad

Connect with me:

https://www.linkedin.com/in/md-ali-azad/

Languages and Tools:

android blender bootstrap c chartjs cplusplus css3 django firebase flask git html5 illustrator java javascript linux matlab mysql opencv oracle pandas photoshop python pytorch scikit_learn seaborn selenium sqlite tensorflow unity

md-ali-azad

Β md-ali-azad

md-ali-azad

Md Ali Azad's Projects

basic-computer-graphics-algorithms-implementation-in-python icon basic-computer-graphics-algorithms-implementation-in-python

Explore fundamental computer graphics algorithms implemented in Python. This repository contains a collection of Python scripts and code examples for essential computer graphics concepts, making it a valuable resource for learning and applying graphics fundamentals.

bhcr-using-dconvaennet icon bhcr-using-dconvaennet

In this paper, we introduce an Autoencoder with a Deep CNN, which we call DConvAENNet for recognizing Bangla Handwritten Character (BHC). A total of 22 experiments were performed on the three-character datasets (BanglaLekha-Isolated, CMATERdb 3.1, Ekush).

code_breakers_nsu icon code_breakers_nsu

At the NSU Inter-University Hackathon 2020, we took on the challenge of developing a web application that addressed the needs of both vendors and buyers. Our team proudly achieved the distinction of being the first to successfully tackle this challenge.

crack-detection-in-sanitary-ware-products-ceramics-using-yolov4 icon crack-detection-in-sanitary-ware-products-ceramics-using-yolov4

This project leverages the power of YOLOv4, an advanced object detection algorithm, to identify and locate cracks in ceramic sanitary-ware products in real-time. This cutting-edge solution employs deep learning techniques to enhance the quality control process.

seclms icon seclms

SEClms is a web-based digital library management system application that is built using the Django framework. It is designed to help librarians manage their digital collections more efficiently and provide students with easy access to the library’s resources.

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