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Hi there, I am Tajamul Bashir πŸ‘‹

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  • ⚑ Fun fact: The first rule of programming- if it works, don’t touch it.πŸ€“

About Me

  • Β  πŸ‘¨πŸ»β€πŸ’» I am a Machine Learning and Artificial Intelligence Enthusiast
  • Β  πŸŽ“ Pursuing Undergraduate in CSE.
  • Β  🌱 Learning and exploring Deep Learning.

Tech Stack

  • 🌐 Β  Python Cpp HTML5 CSS3

  • βš™οΈ Β  GitHub Tensorflow PyTorch OpenCV

  • πŸ”§ Β  Visual Studio Code

    tajammulbasheer

Show some  ❀️  by starring some of the repositories!

Tajamul Bashir Najar 's Projects

deeplizard-keras icon deeplizard-keras

This repository contains the notebooks, I created while learning Keras from DeepLizard. It contains cat vs dog classification notebook and sign language clasification notebook.

face-mask-detection icon face-mask-detection

The is simpler project exploring the problem of face mask detection and developing a model using transfer learing with vgg19 implementing with using keras, tensorflow and opencv frameworks to make predictions on images, videos, and realtime video.

facial_emotion_detection icon facial_emotion_detection

Our facial emotion detection model employs deep learning to discern and classify human emotions from facial expressions. It offers real-time emotion recognition, image analysis, and the flexibility to train custom models. With a focus on accuracy and versatility, our model opens up exciting possibilities for emotion-aware applications and services

gan-for-mnist icon gan-for-mnist

The project involves utilizing Generative Adversarial Networks (GANs) to generate fake MNIST images. GANs are a class of machine learning models consisting of two components: a generator and a discriminator., which are implemented here using PyTorch framework.

sign-language-digit-classification icon sign-language-digit-classification

This project is a recreation of an existing sign language digit classification system, with the goal of learning and experimenting with different machine learning models and tools. The project uses various models, including logistic egression, SVM, decision trees, passive aggressive classifiers, SGD classifier, KNN, perceptron, and ensemble methods

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