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Shahzaib A. AI, Cloud and Data Platforms

My name is Shahzaib A. and I have over 6 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Data Science, TensorFlow, Python, Flask, etc.. I hold a degree in Bachelor of Science (BS), Master's degree. Some of the notable projects I’ve worked on include: JobSiteSentery Project, MoonMetaVerse NFT's Market Place, Ooder recommendation ecommerce platform(Web and Mobile Apps), Covid 19 SOP's Measurement., EWSOM, etc.. I am based in Phoenix, United States. I've successfully completed 8 projects while developing at Devaims.

I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.

The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Devaims, I leverage these skills daily to build resilient systems that stand the test of time.

I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.

Main Technologies

  • Machine Learning
  • Data Science
  • TensorFlow
  • Python
  • Flask
  • Deep Neural Network
  • Amazon Web Services
  • Big Data
  • Django
  • ETL Pipeline
  • Docker
  • RESTful API
  • PostgreSQL
  • Web Application
  • Data Analysis

Notable Projects

JobSiteSentery Project

This project is to build a smart cam that can easily detect intrusion activity in front of the camera. requirements are to compute all the detection and motions on client edge devices So We have worked on several edge computing devices like pie4 with coral edge TPU, jetson nano, TX2, Coral Dev board. We have used the TensorFlow lite version to deploy all the solutions to save the server-side cost. These devices are really time savers and speed up the whole inference, frame, and detection time.

MoonMetaVerse NFT's Market Place

Grise finance is NFT based marketplace where we can hold some tokens to utilize all of the services for free. The services include NFT's digital art, find an investment opportunity, top trend on social data and analytics report, cash flows, ROI, Artificial Intelligence Indices of currency, sentiment analysis, etc.

Ooder recommendation ecommerce platform(Web and Mobile Apps)

Ooder is an e-commerce marketplace where we can purchase the product at the best minimum price from top product providers in the UK. This helps users to find the price using AI and see similar product ingredients. Furthermore, this platform is designed in a way so every user can have their own personalized screens behind the scene I have built multiple recommendation techniques(collaborative and content filtering) on the based of profiles and products to suggest something relevant and to get the most out of it. My role in this project is as a full-stack data scientist. Mobile and Web Application play.google.com/store/apps/details? id=com.jordan.ooder&hl=de&gl=US

Covid 19 SOP's Measurement.

This project is trained on open-source data with some pre-trained transfer learning models. Features Including distance measurement, face detection, mask detection and general coco objects detections

EWSOM

This product is built to analyze the different marketplace, find top social trends, Analysis of hashtags, and with trending keywords. Furthermore, I have built different word clouds to find the relationship between the data and users.

Social Text Analysis Platform

This project represents all the strategy for the classification of data using advanced algorithms like NB, SVM, LSTM based on three states; negative, positive, neutral. We use AAVN (Adverb-Adjective-Verb-Noun) combination method to analysis the social media data for sentiments. We separate all the data of into negative or positive result to convert it into pattern or knowledge based and make it valuable for client in choice making

Gsmarena Mobiles Reviews Analysis

Feature: ✔️ Recommend the list of Mobiles to User according to analysis. ✔️ Analysis of all the opinion about selected one. ✔️ Generate the final report with mobile positive and negative data analysis.

GroundSchoolAI

The idea behind this project is to provide education, available globally for students to always learn new things and keep up to date according to market. Abstract Product features:- ✔️ Artficial intelligence is use to track user data for recomenations. ✔️ Provide solutions and find the weak area of student. ✔️ Improve each user expertise. Use AI to find and build Solutions. Easy to use and flexible for all users. My Roles:- ✔️ Back-end Flask api's ✔️ Artificial Intelligence Model ✔️ Microservices with docker container and use kong as api gateway to manage all microservices. ✔️ All user data menage on Spark number of database are used to manage data like neo4j for finding hidden patterns and relation among the data node of each user. ✔️ Kafka for event management for each user to manage test case.Real time logs events of user also managed by using kafka.

Education

  1. Bachelor of Science (BS), SOFTWARE ENGINEERING

    University of Management and Technology · 2014 – 2018

  2. Master's degree, DATA SCIENCE

    Friedrich-Alexander-Universität Erlangen-Nürnberg · 2021 – 2023

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Services

Solutions

  • Ecommerce
  • Blockchain
  • AI
  • AR/ VR

Technologies

  • React Native
  • Flutter
  • Python
  • Javascript

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