Mo.Ausaf

About Me Hey Visitor, 🫡 I'm passionate about machine learning and dedicated to transforming data into solutions. With a curiosity for the unknown and a love for code, I harness the power of AI to solve real-world challenges.

Get to know me!

I'm a student based in India. I've worked on Machine Learning, Computer Vision and NLP projects.

Being born and brought up in around 4 Indian states, I happened to know guys who know guys. With both my technical abilities and love to get to know people smarter than me, I am excited about the opportunity to learn, grow and contribute my skills and knowledge to the world. With my educational background and interests, hands-on experience in machine learning projects, and passion for continuous learning, I want to mak a positive impact.

and, oh, I happened to like rubik cubes too, all shapes and sizes.
Feel me ? then ping me for work, an idea or maybe even better, just Chit-Chat ! ☕

Reach Me

My Skills

C++

Python

NumPy

Pandas

MatPlotLib

Sci-Kit Learn

Tensorflow

OpenCV

Google Colab

Git-GitHub

SQL

OOPS

Web-Scraping (Beautiful Soup)

My Coursework

Statistics and Probabilty

Calculus

Operating Systems

Design and Analysis of Algorithms

Object Oriented Programming

Database Managment Systems

Web Technolgy Basics

Machine Learning Techniques

Certifications and Courses

Algorthimic Toolbox - University of Michigan via Coursera icon

Object Oriented Data Structures in C++ - University of Illinois at Urbana-Champaign via Coursera icon

Programming for Everybody - University of Michigan via Coursera icon

Projects During my Learning, I have worked on many Projects, some interesting ones of them are :

Deep Learning based Medicinal Plants Detection

This project aimed to identify medicinal herbs using a machine learning model(s). The model used ResNet, a type of CNN, with a validation accuracy of 96%.

Case Study

CV-Repcounter-Timer

This project involved using Media Pipe's pose detection system to count the reps done by a subject. The model calculates the angle between body parts and registers a recount based on a threshold with speial emphasis on filtering fluctuation of feed in real time.