Omdena Chapter Page: Pakistan

Omdena Pakistan Chapter - Omdena Chapters

Welcome to the Pakistan Local Chapter!

Apply here to be a chapter lead for other cities and/or universities in Pakistan.

Upcoming Projects

Lahore, Pakistan Chapter

Project Starts: August 25th, 2022 

Duration: 4 Weeks

Building an Interactive Dashboard to Report and Analyze the Relationship Between Recent Inflation in Food Prices and The Increased Crime Rate Within Pakistan
Lahore, Pakistan Chapter Lead – Emaan Mujahid

 

The background:

Recently, there has been a surge of inflation in Pakistan. This has had a series of adverse effects on the livelihood and economy of the people. The purpose of this project is to gather and search for data from various sources and perform an Exploratory Data Analysis and understand the trend in the rising prices over the years. We will also build a potential web scraper to extract this information if it is needed. We will further explore the process of building effective and interactive data visualisations to display the data. We will build and deploy an interactive dashboard to display the results.

 

The issues:

We need to gather relevant data related to the project. We will analyse the trends in the data. This project aims to tackle the issue of scarcity of relevant data related to this issue and aims to research on and build interactive visualisations.

 

The goals of the project:

1. Using various visuals, analyse the trends in food prices and crime rate.
2. Work with databases and build a web scraper if needed to extract relevant data.
3. Build and deploy an interactive dashboard.
4. building rest apis and an interactive web app to display the results.

 

The learning outcomes are as follows:

1. Collection of Data.

2. Exploratory Data Analysis.

3. Building insightful Data Visualisations.

4. Build REST API with Flask.

5. Dockerizing and deploying a Web Application.

 

The tasks & timeline:

Week 1

– Understanding of Problem Statement.

– Data gathering.

– Building web scraping scripts.

Week 2

– Exploratory Data Analysis(EDA).

– Building Dashboard & Visualisations.

– Introduction to REST APIs & Web Applications.

Week 3

– Building Backend API.

– Building Front-end.

– Workshop on Docker And Docker Compose.

Week 4

– Finish Integrating Web App.

– Deploy the App in Cloud Application Platforms.

 

Lahore, Pakistan Chapter

Project Starts: September 26th, 2022 

Duration: 5 Weeks

Using NLP to Build a Mental Health Chatbot for Low Resource Languages
Lahore, Pakistan Chapter Lead – Emaan Mujahid

 

The background:

Pakistan is home to a plethora of low-resource languages. Mental health issues are a pertinent issue people in Pakistan are facing these days, however, due to the stigmas associated with this topic, it remains largely ignored. This project aims to tackle this issue, by building a first of its kind urdu based mental health chatbot. This project will be a vibrant addition to the work promoting the development of low-resource languages, and will also address the issue of mental health issues by building a compassionate NLP-based model that can hold personalized textual conversations with its users.

 

The issues:

We will need to gather an urdu based dataset that can be done by using newspaper sources. We will further use NLP techniques to build the model. Furthermore, we will build and deploy a dashboard to display the results.

 

The goals of the project:

1. Gather Urdu-based data.
2. Develop a chatbot model.
3. Develop visualizations.
4. Deploy the app.

 

The learning outcomes are as follows:

1. Collection of Data.
2. Pre-processing of Data.
3. Modelling.
4. Model deployment into a possible API.
5. Visualisation.

 

The tasks & timeline:

Week 1

– Data Collection (pre-week 1 even).

– Data Pre-Processing.

Week 2

– Building model.

Week 3

Building model and visualization.

Week 4

Building and deploying the app.

Week 5

– Preparing final documents and results.

 

Completed Projects

AI Applied: Reducing the Energy Crises in Pakistan with Machine Learning
1st Challenge Completed

 

The Problem 

Pakistan has a population of 224m people yet only half have access to 24/7 electricity. Without electricity, there are no computers or the internet. There are no fridges to keep food fresh. There is no electric water pump. There is nowhere to charge a mobile phone.

Schools and Hospitals struggle to provide basic services. Widening electricity access is an essential first step for improving education, healthcare, and local economies.

Centralized planning for electricity in Pakistan has failed. The government has built-in failure by fixing prices and profits; there is widespread corruption, and banks will not lend to new power plants. Meanwhile, half the existing plants lie idle, and the rest operate below capacity.

Millions live under the grid but not connected to it; previously connected but some equipment failed and has not been replaced, or they have electricity but only enough for a light bulb; or they have it, but it is unreliable due to daily power cuts.

The Project Goals

1. To find target sites we need to exclude those that already have electricity. In addition, those close to the grid were given low priority as they are more likely to receive it directly in the future. The volume of available and free satellite data is incredible. There are night-time light images that clearly show towns that have light.

2. But how do we validate that? Here we can leverage the magic of google maps. I find it awesome to be able to zoom in on a road in Pakistan to see whether it has streetlamps. Based on a selection of test towns it was possible to calibrate and validate the data from satellite images.

3. For the electricity grid, you may think the government and electricity companies would know where their cables are. But they do not!

4. Fortunately, we could leverage an existing model to identify electricity cables that used a combination of machine learning on satellite images and human checking.

 

The Learning Outcomes

1. Data Extraction

2. Data preprocessing

3. Data Annotation

4. Classification with ML Models

5. Data Visualization

Project Application: https://renew-rho.vercel.app/

Source Code: https://github.com/OmdenaAI/omdena-pakistan-energy-crisis

Link to the Original project: Harnessing AI for Renewable Energy access in Africa

COVID'19 Analysis in Pakistan
2nd challenge completed.

 

The Background

The economic impact of the COVID-19 pandemic in Pakistan has been largely disruptive. According to the Ministry of Statistics, Pakistan’s growth in the fourth quarter of the fiscal year of 2020 went down by 3.1%.

If we could map the shortage and unavailability of vaccines across various states in Pakistan vs the wastage of vaccines across the country, this could help in increasing the efficiency of the vaccination. The current total vaccinated Pakistani across the whole country (shown below), (by our World in Data)

A large proportion of the covid19 mortality rate in Pakistan is because of failing to early identify the presence of coronavirus and its symptoms. Identifying symptoms of Covid19 and mapping its severity level not only help diagnose the viral disease faster and efficiently but also help to reduce the mortality rate by getting medication much sooner.

 

The Problem

In this 4-weeks project, the goal is to build a model to analyse and model the change in economic trends over the past couple of years in Pakistan due to the outbreak of covid and correlate it with various factors that contribute to the rise and fall of the economy. The NLP-based model can then be used to predict the change in future trends in the economy based on these factors. The sentiment of people is modelled from the historical data which can then be used to predict the real-time sentiment and the factors contributing to that sentiment when a potential third wave or a new outbreak happens within the society.

Other objectives include building computer vision models to early detect the presence of covid through X-ray images or CT scans and classify the severity of Covid-19. The project will be made open-source and the results obtained can help create awareness about the spread of Covid19 and its impact on the Pakistan economy. The final tracker and the dashboard made can be used as a tool to track vaccine availability across various states

 

The Project Goals

Economic Impact of Covid19 in Pakistan

1. Collect covid related data from the various up to date sources

2. Data Pre-processing and Exploratory Analysis

3. An interactive Plot /Map displaying current covid analytics of each state.

4. Forecast the relation between covid vs economic change in past time and estimate the effect of covid in the future through Time-series analysis.

Shortage and wastage of Covid19 vaccines 

1. Gather and pre-process the available public open-source data on the latest statistics on Covid19 vaccines.

2. NLP-based Tracker to track the vaccinated population.

3. Interactive Dashboard showing the stepwise-wise statistics of active cases, death cases are given the time range, age-group specific distribution.

4. Correlation matrix between total people vaccinated vs total vaccine produced.

5. Correlation matrix between coronavirus (Covid-19), mortality and morbidity rate, burden over radiologists.

6. A Knowledge Graph-based solution to visualise the state-wide shortage and availability of COVID19 vaccine.

Early prediction of Covid19 Through Computer Vision

1. Predict the likelihood of covid positivity from chest CT Scan images and respiratory patterns. From demographic and clinical data (the patient’s age and sex, exposure history, symptoms, and laboratory tests) were put into a machine-learning model to classify COVID-19 positivity.

2. Using model predictions to track patient recovery from Multiple CT scans taken during treatment can be used to analyse whether the patient is recovering or worsening.

3. A web application to visualize the severity of covid from chest X-ray images.

 

The Tasks & Timeline

Week 1 Week 2 Week 3 Week 4

– NLP text Pre-processing

-Twitter Hashtag extraction

-Image pre-processing

– Exploratory Data Analysis (EDA)

-Interactive plots with Real-time data

-Interactive map vaccination tracker 

-Classification model based on covid symptoms

-Sentiment Analysis Model 

-Image Classification model based on symptoms

-Start building Streamlit WebApp

-Finish Integrating WebApp

-Deploy the App in Cloud Application Platforms

 

Learning Sessions and Timeline:

1. EDA Workshops: Starts from Sept 25th

2. Streamlit Bootcamp: Starts from 11th Oct

 

The Learning Outcomes

1. Data Pre-processing

2. NLP based EDA

3. Developing and Deploying Dashboards

4. Time Series Forecasting

5. Computer vision and model Building

 

Source code 

https://github.com/OmdenaAI/omdena-pakistan-covid-analysis


Dashboard

We will be running an AI project soon…. Stay Tuned!

Pakistan Chapter
 
Pakistan Chapter Leads

Qasim Hassan

Qasim Hassan is a student/entrepreneur visionary passionate individual with a strategic mindset toward  Artificial Intelligence & Data Science. He is a Jr. Machine Learning Engineer at Omdena and formally a Jr. Data Scientist at AISOL.

Emaan Mujahid

I am a tech enthusiast, who strives to find software-based solutions for various issues pertaining to a variety of topics, particularly in the domain of Language and Speech Technologies. I hold a particular interest in researching various techniques to improve data visualization and build systems for the efficient deployment of models to software-based systems. I am currently working as a researcher, with a focus on deep fake audios. I am also heavily involved in the development of software systems.

Syed Arsalan Amin

A data scientist who loves to tackle complex data science problems using machine and deep learning. Always ready to catch opportunities and keep me engaged to be a professional. Solves problems with dedication and entrepreneurial spirit to draw meaningful conclusions and gain insight into the data provided.

Our Partner(s):