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Kamal H. - Fullstack Developer, NLTK, Big Data

At Softaims, I’ve found a workplace that thrives on collaboration and purposeful creation. The work we do here is about more than technology—it’s about transforming ideas into results that matter. Every project brings a mix of challenges and opportunities, and I approach them with a mindset of continuous learning and improvement. My philosophy centers around three principles: clarity, sustainability, and impact. Clarity means designing systems that are understandable, adaptable, and easy to maintain. Sustainability is about building with the future in mind, ensuring that the work we do today can evolve gracefully over time. And impact means creating something that genuinely improves how people work, connect, or experience the world. One of the most rewarding aspects of working at Softaims is the diversity of thought that every team member brings. We share insights, question assumptions, and push each other to think differently. It’s this culture of curiosity and openness that drives the quality of what we produce. Every solution we deliver is a reflection of that shared dedication. I’m proud to contribute to projects that not only meet client expectations but also exceed them through thoughtful execution and attention to detail. As I continue to grow in this journey, I remain focused on delivering meaningful outcomes that align technology with purpose.

Main technologies

  • Fullstack Developer

    5 years

  • Machine Learning

    4 Years

  • Data Science

    2 Years

  • AI Model Training

    1 Year

Additional skills

  • Machine Learning
  • Data Science
  • AI Model Training
  • Deep Learning
  • Federated Learning
  • Python
  • Django
  • Flask
  • Forecasting
  • Machine Design
  • R
  • Apache Hadoop
  • Apache Spark
  • NLTK
  • Big Data

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Experience Highlights

Sentiment Analysis Model for Reviews Using Machine Learning & GCP

This project aims to develop a robust sentiment analysis model to classify customer reviews as positive, negative, or neutral. Using machine learning and Google Cloud Platform (GCP), we will process large volumes of textual data to provide actionable insights. Businesses will benefit from an improved understanding of customer sentiment, leading to enhanced products, services, and brand perception.

Expert System for Diagnonis Diesease

The provided Prolog code implements an expert system for determining emergency case levels and providing appropriate advice based on patient responses to a series of questions. The system is structured to ask questions about the patient's symptoms and condition, then analyze the responses to assess the severity of the situation and offer corresponding guidance. Here's how the system works: 1. The `ask_question/2` predicate prompts the user with a question and reads their response (either "yes" or "no"). It validates the input to ensure it matches the expected format. 2. The `validate_answer/2` predicate checks if the user's input is valid ("yes" or "no"). If the input is invalid, it fails, prompting the user to provide a correct response. 3. The `determine_emergency_case/2` predicate orchestrates the questioning process. It begins by asking about the patient's shortness of breath and proceeds to ask additional questions based on the responses to determine the severity of the emergency case. Depending on the symptoms reported, it assigns an emergency case level and provides corresponding advice for handling the situation. 4. The `start_expert_system/0` predicate serves as the entry point for executing the expert system. It initiates the questioning process, determines the emergency case level and advice, and displays the results. To use the system, the user simply runs the `start_expert_system/0` predicate, which guides them through the questioning process and provides recommendations based on the input provided. This expert system can be a valuable tool for individuals to assess emergency situations and take appropriate actions based on the severity of the case and the specific symptoms observed. It can help users make informed decisions and potentially save lives in critical situations.

Breast Cancer Prediction Application

In my recent project, I undertook the pivotal task of developing a state-of-the-art deep learning model for the detection of breast cancer Breast cancer is a disease that, while boasting a lower mortality rate compared to some other diseases, significantly influences the quality of life due to the abnormal growth of malignancy cells in the body. The primary goal of this project was to tackle the pressing issue of misdiagnosis that plagues the field of breast cancer diagnosis. Many patients face a dilemma when it comes to accurately identifying the type of breast cancer infection they have.

Stack Warfare: Death Stacks

Welcome to "Stack Warfare: Death Stacks," an exhilarating game development endeavor that brings strategic gameplay to the forefront. This project introduces players to an abstract strategy game where tactical thinking and calculated moves take center stage. The ultimate objective? Conquer the board by skillfully stacking your game pieces until all the stacks belong to you! Game Overview:"Stack Warfare: Death Stacks" is an abstract strategy game played on a 6x6 chessboard. Players command a set of 12 game pieces each, colored red and blue. The game's brilliance lies in its abstract strategy, where players take turns moving their stacks horizontally, vertically, or diagonally. The number of pieces moved determines the distance of the move, and the top piece of the stack determines ownership. Game Mechanics: Players have the freedom to move their stacks in straight lines, with movements mirroring at the board's edges.Stacks can be strategically placed on existing stacks, allowing players to capture their opponents' stacks.The Too-Tall Rule comes into play, necessitating the mandatory movement of stacks exceeding four pieces.Notation and Interface Implementation:This project employs a modified FEN notation to describe the game state and moves accurately. To achieve this, the development process involves implementing seven distinct interfaces. These interfaces encompass tasks such as validating FEN strings, constructing the game board, calculating movement paths, determining winners, listing possible moves, validating moves, and listing executable moves. Project Goals: The primary aim of this project is to implement and rigorously test the specified interfaces. This entails meticulous work in both the src and test folders, all within the realm of Haskell Stack.The project places a strong emphasis on ensuring that functional requirements (FP) and Haskell program coverage (HPC) are met for each of the implemented interfaces.A key component of the project's objectives is the development of a highly efficient and competent bot for "Death Stacks." This task involves working within the provided template.Development Guidelines: Developers working on this project will be expected to closely follow the provided Haskell Stack project template for seamless implementation.The project utilizes Test.HSpec for unit testing. Developers should ensure that the unit tests are fully executable using the command stack test deathstacks:units.To maintain consistency and alignment with project goals, it is crucial to adhere strictly to the given rules and constraints. This includes avoiding any alterations to signatures and validation tests.Project Title: Stack Warfare: Death Stacks Embark on this exhilarating journey as you dive into the world of "Stack Warfare: Death Stacks." This project invites you to create a captivating and challenging abstract strategy game that will undoubtedly captivate players. Showcase your coding prowess as you diligently implement and rigorously test the specified interfaces, guaranteeing a seamless and enjoyable gaming experience. Conquer the intricate challenges of "Stack Warfare: Death Stacks" and elevate your coding skills to new heights!

Education

  • Beaconhouse School System

    High school degree in Computer science

    2017-01-01-2019-01-01

  • Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology

    Bachelor of Computer Science (BCompSc) in Computer science

    2019-01-01-2023-01-01

Languages

  • English
  • Spanish
  • Urdu

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