MHassaanButt/Human_Activity_Recognition_Using_ML-NN

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MHassaanButt/Human_Activity_Recognition_Using_ML-NN

MHassaanButt

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Demonstrate Machine Learning Algorithm and Neural Networks for Human activity recognition using smartphone data. The dataset is from the UCI Machine Learning Repository.

Adove-Photoshop-Free

Adobe Photoshop is a multifunctional external graphics editor from the company for photo processing, creating illustrations, prototypes and layouts for web design, portable animations and much more.

Antenna-design-using-ML

In this project, I applied different regression models for rmse and mae on antenna dataset for predict signal strength.

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Flight-Delays-Prediction

In this project, I used Decision Tree Learning Model as the main algorithm to build the model. Due to the big amount of flight data, we implement the project using MRJob, PySpark and Spark's MLlib then compare the performance and accuracy of those implementations.

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Rice-Disease-Classfication

In this project, I used Hybrid deep CNN transfer learning on rice plant images, perform classification and identification of various rice diseases. I employed Transfer Learning to generate our deep learning model using Rice Leaf Dataset from a secondary source. The proposed model is 90.8% accurate, Experiments show that the proposed approach is viable, and it can be used to detect plant diseases efficiently.

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MHassaanButt

Github home page customization.

Mailing_Merge_Using_Google_API

In this repo, I merge google sheet with google Docs using google API for automation purposes.

Discrete-event-simulation

I designed a network packet routing system. To do so, I define the system and run a simulation so that I can generate data that will be used for the optimization of design parameters.

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Covid_Prediction_based_on_medical_symptoms

In this project I considered several medical symptoms to predict using logistic regression either the person is infected or not and also provide some recommendations to him/her.

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Crime-Spark-ML

In this project I stream data and do crime classification using Spark. This dataset contains incidents derived from the SFPD Crime Incident Reporting system. The data ranges from 1/1/2003 to 5/13/2015. I do some data analysis of crime scenes in different areas and with respect to other parameters.

MathChallenge

Have the function MathChallenge(str) take the str parameter being passed and evaluate the mathematical expression within in. For example, if str were "2+(3-1)*3" the output should be 8. Another example: if str were "(2-0)(6/2)" the output should be 6. There can be parenthesis within the string so you must evaluate it properly according to the rules of arithmetic. The string will contain the operators: +, -, /, *, (, and ). If you have a string like this: #/#*# or #+#(#)/#, then evaluate from left to right. So divide then multiply, and for the second one multiply, divide, then add. The evaluations will be such that there will not be any decimal operations, so you do not need to account for rounding and whatnot.

stats-preview-card

Stats preview card component a challenge by front end mentor

Association-Rule-Mining-using-Apriori-and-FP-Growth

Implementation association rule mining using APRIORI and FP GROWTH using python

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Task-Tracker

Task Tracker build using ReactJs

Trusted-Networks-Based-RS

The aim of the project is to develop recommended systems based on social networks. To find similarity-based between users and compute trust values on different levels of trust. We can extend this work to dynamic levels not fixed to a certain level.

Pulling-Data-from-ESPN-of-NCAAF

In this project, I pull the data of College Football matches play by play.

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profile-card-component

This is a solution to the [Profile card component challenge on Frontend Mentor].

Recipe-App

Developed using ReactJs and Edamam (Recipe Search API)

Dataware-House-Data-Mining-Experimental-Guide-Source-Codes-GuideBook

The aim of this repository to guide the new students who wants to learn how basic algorithms of data mining (Apriori, Kmeans and KNN etc) are implemented

Frequentist-inference-and-regression-modeling

In this project, I am applying your frequentist inference and regression modelling skills to different datasets. I applied several machine learning algorithms and try to answer research questions of related problems and also perform data visualization to justify my results.

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FCHCNN-for-HSIC

This repo is implementation of research article "A Fast and Compact Hybrid CNN for Hyperspectral Imaging-based Bloodstain Classification".

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The_Schelling_Model

The Schelling model of segregation is an agent-based model that elucidates how individual preferences for neighbours might result in segregation. When agents represent householders who relocate to the city, the model is particularly efficient for studying ethnic group residential segregation.

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Brain_Tumor_Classfication_Using_DL

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Plotting-Json-into-Image-with-RLE-Encoding

In this demo project, I read Json and plot image using CV2 by applying RLE encoding and decoding.

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Decision_Tree_On_Multiple_Datasets

The goal of this project is to implement the supervised strategy of the class decision Tree on different datasets.

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mhassaanbutt.github.io

A community maintained open source project aimed at making a personal portfolio for researchers, developers, and analysts simple, fast, and less cumbersome.

real-time-emotion-recognition

A web application for real-time emotion recognition using Vision Transformer (ViT). The app processes video input to generate an output video with an accompanying graph displaying emotion values for each frame.

visionwise

A web application leveraging the Florence 2 model for advanced image captioning and visual question answering. Explore the intersection of AI and computer vision with a user-friendly interface. Contributions are welcome!

finding_prodcutivity_of_diff_departements_using_regression_models

In this case study, we have dataset of a company for case study to find actualy proudcity of its workers using regression models. I draw a comparative analysis of different machine learning algorithms on the basis of mean absolute error.

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Face_Recongnition_using_Deep_Learning_Techniques

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Employee_Data_Management_Project_Using_R

In this project we performed PCA, LDA and Ridge Regression

Impact-of-Covid-on-IT-companies-stock-exchange-shares

We try to analysis the impact of covid 19 on Stock Exchange ( IT companies)

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flask_rest_api

URDU_Sentiment_Analysis

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Grey_Scale_Masks_to_RGB_Conversion

Converting Greyscale Masks to RGB images by assigning each class of mask a color using OpenCV

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Cricket_Predictions

In this project, I predict a winner for the ashes ODI series between England and Australia where the away team is England and the home team is Australia using a machine learning algorithm.

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Netflix-Analysis-using-R

EDA_and_k-means_on_FreshCo_Data

Perform an exploratory data analysis on the data and then use k-means to produce a cluster analysis.

Python_Fun_Scripts

Comparision-of-ML-and-DL-models-for-Cifar-10

I do comparison of KNN, SVM (polynomial and Gaussian Kernel) and CNN (Sequential and RESNET) on Cifar-10 dataset.

Jupyter Notebook

trends-awarness-backend

I have built a backend API in Flask that scrapes data from Twitter based on hashtags and keywords and returns a JSON response. To do this, I installed the necessary Python packages, authenticated with Twitter API, created a Flask app, defined an endpoint for scraping data, parsed the data and returned a JSON response.

Implementing_Different_Trees_Models_on_US_Companies_Data

In this project I implemented decision tree, bagged tree, random forest and XGBoost for comparison of better MAE performance between Trees Algorithms.

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newspaper-scraping

Atomically Newspaper Scrapping Using Beautiful Soup. Only three Categories of news are scraped including national, international and latest. News Summarization, Text Classification, Sentimental Analysis, WordCloud and many more NLP stuff is included.

Calamity_Prediction

In this project I used past three years data of climate having key attributes like rainfall, wind speed, direction, temperature etc and predict calamity on the basis of these key attributes for next year three years using logestic regression technique and also perform descriptive data analysis.

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Uber_Tweet_Scraping_With_and_Without_Emojis

In this project we are scraping 5000 recent tweets with #uber using r langauge and stored in two different dataframes on the basis of emojis are present and not. Then we are going to perform sentimental analysis.