Discover @A-S-A-D-ULLAH Open Source projects

A-S-A-D-ULLAH

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Global Rank 406,458 (Top 15 %)
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Registered over 3 years ago
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Jupyter Notebook
82.4 %

Java
11.8 %

HTML
5.9 %
Location 🇵🇰 Pakistan
Country Total Rank 943
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Jupyter Notebook
59

Java
500

HTML
1,380

Weather-classification-using-machine-learning

Weather classification is a machine learning project in which we predict the weather of different place in the world according to longitude and latitude. For classification we use 5 classification algorithm for this purpose. This is a complete project and Activity diagram is also included.

Jupyter Notebook

Face-Detection-using-OpenCV

In this I will show, how we can use python opencv image processing library to detect faces, draw rectangle around faces and crop faces in jupyter notebook.

Jupyter Notebook

Gender-Detection-using-OpenCV

Gender detection is one of the popular computer vision applications. When you use a camera to detect a person’s gender instead of detecting it on a picture, it can be said to be a realtime gender detection system. I hope you liked this article on Realtime Gender Detection using Python. Feel free to ask your valuable questions in the comments section below.

Jupyter Notebook

Covid-19-Detection-using-chest-X-Ray

In this project we detect Corona virus through chest x-ray. We have dataset of positive and negative x-ray images. So we use sequential model. If you give image of x-ray it will extract feature from it. Then on those feature it predict the result. Second model we trained is also sequential model in which we did the layers tunning.

Jupyter Notebook

Bitcoin-price-prediction-using-machine-learning

Predicting the price of cryptocurrencies is one of the popular case studies in the data science community. The prices of stocks and cryptocurrencies don’t just depend on the number of people who buy or sell them. Today, the change in the prices of these investments also depends on the changes in the financial policies of the government regarding any cryptocurrency. The feelings of people towards a particular cryptocurrency or personality who directly or indirectly endorse a cryptocurrency also result in a huge buying and selling of a particular cryptocurrency, resulting in a change in prices.

Jupyter Notebook

Real-time-Face-Detection-

In this project we detect faces in real time. I use open cv and harcascade.

gamepython

My-Calculator

LifeCycle_Activity

Watermark-Detection-using-InseptionResnetV2-

This algorithm detect watermark on images. The InceptionResnetV2 is used for detection purpose achieving a great testing accuracy. This model is used for many purposes like housing websites etc.

Jupyter Notebook

Sops-Monitoring-and-Detection-Mask-and-Social-distancing-YoloV3

SOP’s Detection is a modern project in field of computer vision (image processing). Our goal is to detect the humans in the video that are not following the main two SOP’s which are social distancing and face mask. This is completed FYP project contain Frontend as well.

Jupyter Notebook

Crack-Detection-using-Transfer-Learning-ResNet50-

This project is aimed at detecting cracks in images using transfer learning with ResNet50. This project uses a pre-trained ResNet50 model, which has been fine-tuned on a dataset of images containing cracks and non-cracks, to detect cracks in new images.

Jupyter Notebook

Deep_Learning_BWF_Asad_Ullah

Jupyter Notebook

Faulty-Steel-Plates-Detection-using-Machine-Learning

The objective is to analyze the impact of luminosity, sigmoid of areas, pastry, stains, dirtiness, and bumps on defects of stainless-steel plates.

Jupyter Notebook

Predict-age-gender-and-ethnicity-from-image-using-Deep-Learning

The proposed model is to predict a person's age, gender, and ethnicity with a grayscale image of that person.

Jupyter Notebook

Asad-Ullah.github.io

HTML

A-S-A-D-ULLAH

Tweets-Classifications-using-Machine-Learning-and-NLP-techniques-

The goal of this project is to use machine learning algorithms and natural language processing techniques to categories tweets according to their topic. To categories tweets into one of four categories—sports and gaming, business and entrepreneurs, everyday life, and pop culture—we will use logistic regression and Naive Bayes classifiers.

Jupyter Notebook

A-S-A-D-ULLAH

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