Hi, I'm Faizan Dhankwala.

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Program Manager, Full Stack Developer, and Machine Learning Enthusiast, with knowledge in C++, Java, Python, React, Node.js, I combine technical expertise with leadership skills to drive successful project outcomes, innovate web solutions, and advance machine learning applications.

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About Me.

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I'm passionate about coordinating software development teams, optimizing resources, and ensuring the successful completion of projects, all while driving organizational growth and innovation through cutting-edge software solutions and machine learning advancements.

  • My Skills Are: Project/Product Management, HTML, CSS, JavaScript, React, Node.js, Machine Learning, YOLO, Makesense.AI, Google Collab, Git & GitHub, Bootstrap, Java, C++, and Adobe Suite.

  • My Weaknesses Are: Taking good pictures of myself.
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Strengths

Software Engineering and Machine Learning

I am a dedicated full stack developer and machine learning enthusiast with 3+ years of experience in delivering high-quality software solutions. My expertise spans C++, Java, Python, React, and Node.js. I excel at developing and implementing machine learning models, optimizing algorithms, and creating scalable applications. I am passionate about coordinating software development teams, driving innovation, and ensuring the successful completion of projects that leverage the latest advancements in software engineering and machine learning.

Program/Product Management

I possess 5+ years of experience in program and product management with a strong background in web and backend development. I have a proven track record of architecting and implementing scalable, efficient, and secure solutions that enhance user experiences and drive business success. My expertise includes coordinating cross-functional teams, optimizing project resources, and ensuring the successful delivery of complex projects on time and within budget.

UI/Web Development

I am a UI/web developer with expertise in React, Node.js, and other modern web technologies. With over 5 years of experience, I have a strong background in UI/Graphic design, dedicated to crafting visually captivating and user-centric designs. My focus is on creating engaging user experiences that contribute significantly to brand elevation and business success. I excel at translating design concepts into functional and responsive web applications, leveraging the latest tools and frameworks to deliver high-quality solutions that meet client requirements and exceed expectations.

Personal Projects.

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App

Basic ChatBot

This chatbot program/interface allows users to interact by typing messages, which are processed using fuzzy matching techniques to identify relevant questions stored in its knowledge base. Upon receiving a message, the chatbot searches for the closest match in its database. If a match is found, it retrieves and displays the corresponding pre-defined answer (using json). For unrecognized enteries, the chatbot prompts users to provide new responses, which it integrates into its knowledge base for future interactions. Overall, a very simple chatbot that replicates AI using memory and json storing.

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App

WeatherApp

A cutting-edge weather application built with HTML, CSS, and JavaScript that empowers you to access real-time weather information for any city across the globe. This sleek and user-friendly weather app goes beyond just providing forecasts; it offers an immersive and interactive experience to keep you informed and prepared for any weather conditions. Key Features: Global Coverage: This weather app offers worldwide coverage, allowing you to check the current weather in any city, town, or village across the planet. User-Friendly Interface: With a clean and intuitive design, this app ensures that accessing weather information is a breeze. Simply enter the city name, and the app will do the rest. Real-Time Updates: Stay up to date with the latest weather conditions as the app provides real-time updates, including temperature, humidity, wind speed, and more. Cross-Platform Compatibility: Access the app on various devices and browsers, ensuring you can check the weather no matter where you are.

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Website

Aesthetic Clock

a minimalist, aesthetically pleasing clock created with HTML, CSS, and JavaScript. This elegant clock combines simplicity and style to offer you a delightful and functional time-telling experience. Key Features: Clean and Elegant Design: Our clock features a beautifully crafted interface with a focus on simplicity. The sleek design ensures that it complements any setting, whether it's on your desktop or as part of a web page. Accurate Timekeeping: The clock provides precise, real-time updates to keep you in sync with the current time, ensuring you never miss a beat. Lightweight and Fast: The clock is designed for efficiency, ensuring it doesn't slow down your website or consume excessive system resources.

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Website

Streetwear Clothing Website

A mockup clothing website created by experimenting with layout using the power of Bootstrap, HTML, and CSS. Please note that this website is for practice and layout experimentation only, and no actual orders can be placed. Key Features: Bootstrap-Powered Responsiveness: Our website is built on Bootstrap, ensuring a fully responsive experience. Whether you're on a desktop, tablet, or smartphone, the website adapts seamlessly to your screen size. Fashion Gallery: Explore the Fashion Gallery, where you can find stunning images of models/cars showcasing style and culture. This gallery was built on bootstrap.

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Application

Face Detection and Expression Using Machine Learning *Use Microsoft Edge*

This program utilizes JavaScript libraries and machine learning to create a web-based face identification and emotion recognition tool. It sets up a webpage with a video element for live webcam feed. The JavaScript code likely handles initializing the webcam, detecting faces, and analyzing emotions using machine learning models. CSS styling ensures a visually appealing layout, possibly with overlays to highlight detected faces. Overall, it offers an interactive platform for real-time face analysis, with potential applications ranging from entertainment to practical use cases like mood tracking or user engagement analysis.

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Application

Rocket League Object Detection

The project involved creating an image dataset by capturing screenshots from a specific window using Python libraries like numpy, win32gui, and PIL, then labeling the dataset using Make Sense AI for manual annotations. After organizing and labeling the images, the dataset was used to train a YOLOv4-tiny object detection model on Google Colab, leveraging pre-trained weights and a custom configuration. Post-training, the model was tested in real-time on a live window of the "Rocket League" game, detecting objects like the ball and boost. While the model showed reasonable accuracy, particularly with static or slow-moving objects, it struggled with fast-moving scenes and varied lighting conditions. The project demonstrated the practical implementation of object detection, including dataset preparation, model training, and real-time application, highlighting challenges in dynamic environments and emphasizing the iterative nature of machine learning development.

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Application

Diabetes Prediction with Machine Learning

This program predicts whether a patient has diabetes using an SVM classifier based on medical attributes such as pregnancies, glucose levels, and BMI. It involves loading and analyzing a CSV dataset, standardizing the data, splitting it into training and test sets, and training the model. The model's accuracy is evaluated, and a predictive system is demonstrated by inputting patient data to predict diabetes status.

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Application

House Price Prediction using Machine Learning

This project is all about visualizing the comparison between actual and predicted prices using a scatter plot to evaluate the performance of my predictive model. I created a scatter plot that includes actual prices on the x-axis and predicted prices on the y-axis, with each point representing a data instance from the training set. By examining this scatter plot, I can assess the model's accuracy by observing how closely the points align with the ideal line 𝑦 = 𝑥. Deviations from this line highlight discrepancies in predictions, providing insights into areas where the model may need improvement. This visualization helps me identify systematic errors and guides further refinements in the model, ensuring continuous improvement in prediction accuracy. To make this process easier, I've included a detailed code example using Python and Matplotlib to create the scatter plot. This example demonstrates how to implement the visualization and understand the model's performance effectively. By using this scatter plot, I aim to provide a clear and intuitive understanding of how well the predictive model works and where it can be improved.

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GUI APP

Java Personality Quiz Test

The Java GUI Personality Quiz Game is an interactive application designed to engage users in exploring various personality types through a fun and educational quiz format. Developed using Java's Swing framework, the program presents users with a series of questions, each accompanied by multiple-choice answers. Based on their responses, the application calculates and reveals the user's personality type from six predefined categories. Each personality type comes with a descriptive text highlighting its unique traits, an associated image for visual representation, and background music that enhances the experience. Users can enjoy discovering different personality types in a visually appealing and intuitive interface, making it both entertaining and insightful. I honestly had a lot of fun making this application!

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Machine Learning App

Predicting Calories Burned Using Machine Learning

This machine learning program employs the XGBoost algorithm to predict calorie expenditure during exercise using a dataset that includes physiological and exercise-related metrics such as age, gender, height, weight, exercise duration, heart rate, and body temperature. By leveraging these features, the model learns patterns that relate these variables to the calories burned, offering insights into how different factors influence energy expenditure during physical activities. This predictive capability can be instrumental in tailoring personalized fitness plans, optimizing workout routines, and supporting health professionals in advising on exercise intensity and duration for effective calorie management and fitness goals.

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