Hi!

I’M SALMAN FARSHI

Let's begin

My Story

A little bit about Me

I am Salman Farshi, graduated from North South University, a deep learning enthusiast, like to explore different types of technology related to AI/ML, and currently working with different types of deep learning projects

Hobbies And Interests

I have a big heart for pets, and I'm especially fond of my four adorable and friendly cats. Aoshima, Japan's Cat Island, holds a special place in my heart because it's a whole island filled with cats – it's like a dream come true for me.

Additional hobbies and interests:

  • Traveling: Exploring new places and experiencing different cultures is a passion of mine.
  • Sports: I'm a sports enthusiast, playing cricket and football and enjoying the thrill of the game.

Skills

Skills

Programming Languages:

  • Python
  • C
  • C++
  • Swift

Frameworks:

  • Scikit-learn
  • TensorFlow
  • PyTorch

Machine Learning Algorithms:

  • Neural Network
  • Linear Regression
  • Logistic Regression
  • Support Vector Machine
  • KNN
  • Random Forest
  • Decision Tree

Deep Learning Algorithms:

  • GAN (Generative Adversarial Network)
  • Computer Vision
  • CNN (Convolutional Neural Network)
  • Auto Encoder
  • VAEs (Variational Autoencoders)
  • Neural Style Transfer

Applications:

  • Object detection
  • Image Generation
  • Image Segmentation
  • Face Detection
  • Face Recognition
  • Prediction
  • Recommendation System
  • Anomaly Detection
  • Image classification

Web:

  • HTML
  • CSS
  • PHP
  • Django

Database:

  • SQL
  • Firebase

Other Skills:

  • Data Cleaning
  • Data Visualization
  • Feature Selection
  • PCA (Principal Component Analysis)

Development Skills:

  • Native iOS development (Beginning stage)

Professional Working Experience

Company Name:

North South University

Job Title:

Research Assistant

Job Responsibilities:

  • Review latest paper
  • Data Collection and Preparation
  • Experiment Design
  • Model Development
  • Training and Evaluation

Technology / Language Used:

Python, Deep Learning, Computer Vision, Generative AI

Duration:

December 2021 – May 2023 (1 Year 6 months)

Research And Projects

Computer Vision, Deep learning,Yolo

AI Powered Smart Agriculture System

Arable , Non-Arable And Waste Land Detection Using Deep Learning

GitHub Repository
Computer Vision, Deep learning,GAN

Abstruct-art-generationDCGAN

Creating mesmerizing abstract art using powerful Deep Convolutional Generative Adversarial Networks (DCGANs) and the Artbence dataset

GitHub Repository
Computer Vision, Deep learning,Image Segmentation

Risky Building Detection using Deep Learning

This project aims to address the alarming issue of risky buildings in Dhaka city, Bangladesh, by leveraging deep learning technology to detect and identify these buildings from satellite images. By accurately identifying risky buildings,

GitHub Repository
Computer Vision, Deep learning,Yolo,Flask,RestAPI

Deploying custom object detection model using Yolov5 and RESTAPI

This project shows how to deploy deep learning model and solve a small dataset challenge for training and evaluating object detection model using YOLOv5. YOLOv5 is a state-of-the-art object detection algorithm known for its speed and accuracy

GitHub Repository
Machine Learning ,

Predicting the winner of T20 world cup

Machine learning for advanced predection. We have used different types of machine learning algorithm for getting better result. We achieved 64% accuracy in logistic Regression that is very effective for t20 matches

GitHub Repository
Computer Vision, Deep learning,Neural Style Transfer

NeuroART

Paint Neural Style Transformation is a Python-based application that applies neural style transfer to images, giving them an artistic, painted look

GitHub Repository
Computer Vision, Deep learning,Yolo

Pothole detection using yolov4

In this project We tried detect path hole using deep learning tech. In this project I have used yolov4 model and darknet framework.

GitHub Repository
Computer Vision, Deep learning,GAN

FlowerGen-flower Generation using WGAN

This project focuses on using the Oxford Flower dataset to train a Wasserstein Generative Adversarial Network (WGAN) for generating realistic flower images.

GitHub Repository
Swift , iOS,Firebase

ToDo:Daily

activity monitoring apps that would monitor and analysis our daily works using IOS.

GitHub Repository

Say Hi

Services Professional Interests

I am searching for a place where I can put my efforts properly and passionately. Besides working on this amazing technology, I also like to work on different types of technologies that can solve real-life problems

About

love to work on deep learning and artificial intelligence; it is my passion to learn this technology and try to solve real-world problems. I work in this field as if I am doing my favourite things. .

Email

salmanfarshinsu@gmail.com

Call

+8801779989094