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I am a Data Scientist. I believe that AI-ML can be equally used in solving problems of the underprivileged, as delivering piping hot pizzas at homes.
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testing-streamlit-camera-module
August 14, 2023 – August 14, 2023
testing-streamlit-camera-module — GitHub repository
View Projectsound_clustering_visualization_verOne
February 6, 2023 – February 8, 2023
This repo is a streamlit app that records audio in browser, and helps to find the silimlarity between 2 or 3 classes of sound.
View ProjectSound-Cluster-Visualization
February 6, 2023 – February 6, 2023
Sound-Cluster-Visualization — GitHub repository
View ProjectBrainEnTech---dataset-1---funny-vs-boring-videos
August 11, 2020 – August 11, 2020
This EEG dataset is created with the intention of classifying funny vs boring videos over approx 30 minutes. A subject is shown 5 minutes of a boring video followed by another 5 minutes of a funny video. This process persisted over 3 cycles. Brain EEG is aggregated over each second and their corresponding video classes are noted.
View ProjectminiBaymax---A-low-cost-interactive-diagonostic-tool-for-Valvular-Heart-Disease-detection
October 28, 2018 – October 28, 2018
This web application is motivated by Baymax of the animated movie Big Hero 6. It detects Valvular Heart disorder i.e. damage or defect in one of the four heart valves. On the Machine Learning side, I have used AutoML from the deep learning platform H2O. And the interactive application is build in RShiny.
View ProjectExploring-the-non-linear-relationship-between-Crimes-and-GDP-using-Generalized-Additive-Models
August 13, 2018 – August 13, 2018
This repository contains the script and figures of the conference paper selected for presentation at the Latin American Conference of Computationa Intelligence 2018. The abstract of the paper is as follows: Crime is an important social and economic problem of South Africa. Though certain categories of crimes are of serious proportions, yet on aggregate the overall crime situation in the country has considerably improved in the last decade or so. A number of previous studies across other countries have shown a positive or negative relationship between crime and economic growth. On a microeconomic/provincial scale, this paper studies the relationship between various categories of crimes and economic growth using the non-linear modeling technique of Generalized Additive Models. Such a modeling approach helps in understanding how various categories of crimes complexly affect GDP.
View ProjectInteractively-forecasting-Global-temperature-using-R-and-Shiny
April 21, 2018 – April 21, 2018
This work is a extensive interactive visualization as well as forecasting tool to forecast global monthly temperature. Choice of country and state (for which the forecasting is required) is menu driven and based upon dynamic subsetting of data. In addition, various graphs and parameters pertaining to the model builiding, comparison of predicted and actual values and future forecast are all based upon click of the reelvant action buttons. The time series algorithm used is Exponential Smoothing, and fairly good results are obtained for a large combinations of countries and states.
View ProjectEarly-estimation-of-protest-time-spans-Using-NLP-Topic-Modeling
March 6, 2018 – March 6, 2018
Protests and agitations have long used as means for showing dissident towards social, political and economic issues in civil societies. In recent years we have witnessed a large number of protests across various geographies. Not to be left behind by similar trends in the rest of the world, South Africa, in recent years have witnessed a large number of protests. This paper uses the English text description of the protests to predict their time spans/durations. The descriptions consist of multiple causes of the protests, courses of actions etc. Next we used unsupervised (topic modeling) and supervised learning (decision trees) to predict the duration of protests. The results are very promising and close to 90% of accuracy in early predicting of the duration of protests.
View ProjectFacebook_analytics_on_NDTV_using_R_and_Shiny
February 28, 2018 – February 28, 2018
This project is a visual and NLP based interactive analytics to understand what NDTV shares in facebeeok in terms of posts, images, and videos; and how its followers/subscribers react to such postings. It consists of two modules: PART 1: is where NDTV's facebook posts are fetched using the Rfacebook package. The script used in fetching the data is named "ndtv_getPage.R" The data fetched from script is saved as "ndtvpage.rds" Please fill in your app_id and app_secret in the fields marked XXXX. PART 2: The shiny scripts are ui.R and server.R Please set the appropriate paths for the readRDS() and the scan() functions. positive.csv and negative.csv are repository of positive and negative sentiment words.
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a strong interest in applying data science to social and economic problems, particularly within a South African context. This indicates a potential fit for organizations focused on impactful data-driven solutions. The diversity of projects (NLP, time series, sound analysis, EEG) shows a broad curiosity and willingness to explore different domains. However, the projects are predominantly personal and academic, and there is no information on collaborative work or team environments, which are crucial for cultural fit in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to conceptualize and execute data science projects from problem definition to interactive visualization. The focus on real-world problems (crime, protests, health diagnostics) suggests a practical and problem-solving mindset. However, without psychometric test results or interview data, it's difficult to assess specific soft skills like teamwork, stress handling, or communication clarity beyond project descriptions.