IQBALPA

Projects

Quran Online

Quran Online

A platform to read qur’an online

  • Developed a qur’an online platform using Next.js and
  • Implement list of surah, arabic and translation text, and tafsir features
Next.jstailwindcss
Movies Catalog

Movies Catalog

Movies Catalog wtih TMDB API. Enable user to create a watchlist

  • Developed full-stack movies catalog web (frontend & backend), deployed with docker-compose on GCE VM
  • Created user authentication & authorization, search movies, and watchlist features
NestJSNext.jstailwindcssPostgreSQLDockerGCP
Real Time Chat App

Real Time Chat App

A real time chat application that allows users to communicate in real time way

  • Developed a full-stack real time chat web application
  • Created user authentication & authorization, search users, friends, and room-based chat features
NestJSNext.jstailwindcssPostgreSQL
Nani Agritech Landing Page

Nani Agritech Landing Page

Nani Agritech landing page for brief introduction of the company

  • Developed a landing page for Nani Agritech with Next.js and tailwindcss
  • Implement state management with redux
Next.jstailwindcss

Todo App Backend

Todo application to manage your tasks

  • Developed a todo application backend with Go
  • Created CRUD API with user authentication & authorization
  • Implemented dependency injection
PostgreSQLGo

Unsupervised Text Classification

Unsupervised text classification using Lbl2Vec

  • Reproduced a paper about unsupervised text classification
  • Leveraged Lbl2Vec model to classify the unlabeled text to certain topics
Python

Kaggle: Emotion Detection from Text

Emotion detection from text using Tf-idf and Catboost

  • Preprocessed the data by transforming dirty data
  • Utilized tf-idf and BERT to extract the text features as a vector representation
  • Utilized Catboost to develop models and evaluate the its performance
PythonTensorflow

Kaggle: Image Scene Classification

Image scene classification using CNN

  • Developed a plain CNN model to classify the image scene
  • Replicated the ResNet architecture to extract the image features and use it as the model backbone
  • Utilized pre-trained ResNet50 model to improve the model performance
TensorflowPython

EDA: The Ultimate Film Statistics Dataset - for ML

Exploratory Data Analysis on the Ultimate Film Statistics Dataset

  • Preprocessed the data by transforming dirty data, splitting column, and reformat the data
  • Performed exploratory data analysis to understand the data distribution and correlation between features
  • Visualized the data using Matplotlib and Seaborn to gain valuable insights
Python

Kaggle Competition: Spaceship Titanic

Predict the survival of passengers on the Titanic

  • Performed exploratory data analysis to understand the data distribution and correlation between features
  • Preprocessed the data by transforming dirty data, encoding, and scaling the data
  • Utilized Scikit-learn, XGBoost, and Catboost to develop models and evaluate the its performance
Python

Bleached Coral Detection

Bleached coral detection using CNN

  • Developed a deep learning model to detect bleached coral by using CNN
  • Leverage Grad-CAM to enhance the model reliability
TensorflowPython

Fire Image Detection

Fire image detection using CNN

  • Created a deep learning model to predict fire image
  • Replicated the ResNet architecture to extract the image features
  • Achieved 95% on accuracy
TensorflowPython

Netflix Landing Page Clone

Netflix landing page clone using React and tailwindcss

  • Developed a frontend clone for Netflix landing page with React JS as the frontend framework and Tailwind CSS for styling
Reacttailwindcss

Rentspace

Rentspace is a platform to rent a venue or place to organize an event

  • Developed a full-stack web app, with microservices backend
  • Created API gateway for microservices communication
PostgreSQLSpringbootGCPDockerNext.js

HalowBund

HalowBund is a platform to provides information for mothers and toddler

  • Created the frontend with plain HTML, CSS, and Javascript for website. And Flutter for mobile app
  • Built the backend system using Django
DjangoFlutter
Quran Online

Quran Online

A platform to read qur’an online

  • Developed a qur’an online platform using Next.js and
  • Implement list of surah, arabic and translation text, and tafsir features
Next.jstailwindcss
Movies Catalog

Movies Catalog

Movies Catalog wtih TMDB API. Enable user to create a watchlist

  • Developed full-stack movies catalog web (frontend & backend), deployed with docker-compose on GCE VM
  • Created user authentication & authorization, search movies, and watchlist features
NestJSNext.jstailwindcssPostgreSQLDockerGCP
Real Time Chat App

Real Time Chat App

A real time chat application that allows users to communicate in real time way

  • Developed a full-stack real time chat web application
  • Created user authentication & authorization, search users, friends, and room-based chat features
NestJSNext.jstailwindcssPostgreSQL
Nani Agritech Landing Page

Nani Agritech Landing Page

Nani Agritech landing page for brief introduction of the company

  • Developed a landing page for Nani Agritech with Next.js and tailwindcss
  • Implement state management with redux
Next.jstailwindcss

Todo App Backend

Todo application to manage your tasks

  • Developed a todo application backend with Go
  • Created CRUD API with user authentication & authorization
  • Implemented dependency injection
PostgreSQLGo

Netflix Landing Page Clone

Netflix landing page clone using React and tailwindcss

  • Developed a frontend clone for Netflix landing page with React JS as the frontend framework and Tailwind CSS for styling
Reacttailwindcss

Rentspace

Rentspace is a platform to rent a venue or place to organize an event

  • Developed a full-stack web app, with microservices backend
  • Created API gateway for microservices communication
PostgreSQLSpringbootGCPDockerNext.js

HalowBund

HalowBund is a platform to provides information for mothers and toddler

  • Created the frontend with plain HTML, CSS, and Javascript for website. And Flutter for mobile app
  • Built the backend system using Django
DjangoFlutter

Unsupervised Text Classification

Unsupervised text classification using Lbl2Vec

  • Reproduced a paper about unsupervised text classification
  • Leveraged Lbl2Vec model to classify the unlabeled text to certain topics
Python

Kaggle: Emotion Detection from Text

Emotion detection from text using Tf-idf and Catboost

  • Preprocessed the data by transforming dirty data
  • Utilized tf-idf and BERT to extract the text features as a vector representation
  • Utilized Catboost to develop models and evaluate the its performance
PythonTensorflow

Kaggle: Image Scene Classification

Image scene classification using CNN

  • Developed a plain CNN model to classify the image scene
  • Replicated the ResNet architecture to extract the image features and use it as the model backbone
  • Utilized pre-trained ResNet50 model to improve the model performance
TensorflowPython

EDA: The Ultimate Film Statistics Dataset - for ML

Exploratory Data Analysis on the Ultimate Film Statistics Dataset

  • Preprocessed the data by transforming dirty data, splitting column, and reformat the data
  • Performed exploratory data analysis to understand the data distribution and correlation between features
  • Visualized the data using Matplotlib and Seaborn to gain valuable insights
Python

Kaggle Competition: Spaceship Titanic

Predict the survival of passengers on the Titanic

  • Performed exploratory data analysis to understand the data distribution and correlation between features
  • Preprocessed the data by transforming dirty data, encoding, and scaling the data
  • Utilized Scikit-learn, XGBoost, and Catboost to develop models and evaluate the its performance
Python

Bleached Coral Detection

Bleached coral detection using CNN

  • Developed a deep learning model to detect bleached coral by using CNN
  • Leverage Grad-CAM to enhance the model reliability
TensorflowPython

Fire Image Detection

Fire image detection using CNN

  • Created a deep learning model to predict fire image
  • Replicated the ResNet architecture to extract the image features
  • Achieved 95% on accuracy
TensorflowPython