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Faizan A. Web, Backend and General Development

My name is Faizan A. and I have over 1 years of experience in the tech industry. I specialize in the following technologies: Web Development, App Development, Python, PHP, node.js, etc.. I hold a degree in Bachelor of Technology (BTech), Bachelor of Technology (BTech). Some of the notable projects I’ve worked on include: Grocery App, Analyzing Car Sales and Profitability across the states using MySQL, Categorization of Articles using Natural Language Processing and ML, Advanced Computer Vision - Object Detection and Recognition, Neural Networks & Deep Learning, etc.. I am based in Lucknow, India. I've successfully completed 12 projects while developing at Softaims.

I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.

My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.

My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.

Main technologies

  • Web, Backend and General Development

    1 year

  • Web Development

    1 Year

  • App Development

    1 Year

  • Python

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Cognizant Technology Solutions

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Experience Highlights

Grocery App

Wishing Basket is a user-friendly mobile application crafted to enhance the gift-giving experience. Developers utilized Swift and SwiftUI for iOS native development, ensuring a seamless and responsive user interface. The app allows users to create and manage personalized wish lists, facilitating easy sharing with friends and family. Key features include event reminders, item addition from various online stores, and collaborative group gifting functionalities. To support efficient data management, developers implemented Firebase for real-time database solutions.

Analyzing Car Sales and Profitability across the states using MySQL

This project utilizes MySQL to analyze car sales data across various states, identifying trends and profitability metrics. By examining sales figures, market demand, and regional economic factors, the analysis aims to determine which states exhibit the highest car selling potential and profitability. The findings will support strategic decision-making for car dealerships and manufacturers, enhancing their market positioning and resource allocation.

Categorization of Articles using Natural Language Processing and ML

In the dynamic media landscape, InfoWorld requires an automated system to efficiently categorize its extensive archive of articles across topics such as World Affairs, Sports, Business, and Science/Technology. This project aims to build a predictive model using advanced machine learning techniques and Natural Language Processing (NLP) to streamline the article classification process. The solution will ensure timely, accurate, and personalized content delivery, enhancing the platform's ability to meet user preferences and improve content management efficiency.

Advanced Computer Vision - Object Detection and Recognition

This project focuses on developing a face recognition system using Convolutional Neural Networks (CNN) and advanced image recognition algorithms. The system is designed to detect, identify, and classify faces within images. It includes two key components: a face detection model to accurately locate the position of faces within an image, and a face identification model to match and recognize the detected faces against an existing database. The project emphasizes hands-on implementation to build an efficient, real-time face recognition solution for various practical applications.

Neural Networks & Deep Learning

This project comprises two sub-projects: Part 1 involves deploying a neural network to develop a regressor and classifier for a communications equipment manufacturer. Part 2 delivers an image classifier utilizing a neural network to recognize and classify numbers from street-level photographs. This model enhances accuracy in identifying numerical data from real-world images, contributing to improved automated visual analysis. Both parts emphasize leveraging AI for predictive and image classification tasks.

Education

  • BBD University

    Bachelor of Technology (BTech) in Computer engineering

    2017-01-01-2021-01-01

  • BBD University

    Bachelor of Technology (BTech) in Computer science

    2017-01-01-2021-01-01

Languages

  • English