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karimosman89/README.md

Typing SVG - Karim Osman
Typing SVG - Positions

Portfolio Resume LinkedIn Email Google Scholar PyPI

Profile Views GitHub Followers


๐Ÿ’ผ Professional Summary

๐ŸŽฏ Impact-Driven AI & ML Engineer

Results-oriented engineer specializing in:

  • ๐Ÿš€ Scalable ML Systems that process millions of data points
  • ๐Ÿ’ก End-to-End AI Solutions from research to production
  • ๐Ÿ“Š Data-Driven Decision Making with measurable ROI
  • โšก Real-Time Processing with distributed systems
  • ๐Ÿ”ง MLOps & Automation for enterprise deployment

๐Ÿ“ˆ By the Numbers

๐Ÿ’ป 10+ Production ML Models Deployed
๐Ÿ“ฆ 5+ Open Source Packages Published
๐ŸŽ“ Multiple Research Publications
โญ Growing GitHub Community
๐ŸŒ International Project Experience
๐Ÿ† Proven Track Record in AI/ML

๐ŸŽฏ What I Bring to Your Team

๐ŸŽฏ For Employers ๐Ÿ’ฐ For Investors ๐Ÿค For Collaborators
Production-ready ML solutions Scalable AI products Open-source contributions
End-to-end project ownership Technical due diligence Research partnerships
Cross-functional leadership Architecture design Knowledge sharing
Cost optimization strategies ROI-focused development Innovation & ideation

๐Ÿš€ Featured Projects & Impact

๐Ÿ† Flagship Projects

Enterprise-Grade Text Classification

  • โœ… 95%+ accuracy on sentiment analysis
  • โšก Processes 10K+ documents/hour
  • ๐Ÿ”ง Built with BERT, Transformers, PyTorch
  • ๐Ÿ’ผ Use Case: Customer feedback analysis
  • ๐Ÿ“Š Impact: 40% reduction in manual review time

NLP PyTorch Transformers

Predictive Analytics for Financial Markets

  • ๐Ÿ“Š LSTM & ARIMA hybrid models
  • ๐Ÿ’น 85%+ directional accuracy
  • โฑ๏ธ Real-time prediction engine
  • ๐Ÿ’ผ Use Case: Stock price prediction
  • ๐Ÿ“Š Impact: Actionable trading insights

TensorFlow Time Series LSTM

Cloud-Native MLOps Architecture

  • ๐Ÿ—๏ธ Fully automated CI/CD pipeline
  • ๐Ÿ“ฆ Containerized deployment (Docker/K8s)
  • ๐Ÿ“Š Handles 1M+ predictions/day
  • ๐Ÿ’ผ Use Case: Customer churn prediction
  • ๐Ÿ“Š Impact: 30% reduction in customer attrition

AWS Docker MLOps

Distributed Streaming Architecture

  • โšก Sub-second latency processing
  • ๐Ÿ“Š Processes TB+ data daily
  • ๐Ÿ”ง Kafka + Spark streaming
  • ๐Ÿ’ผ Use Case: Log analytics & monitoring
  • ๐Ÿ“Š Impact: Real-time anomaly detection

Kafka Spark Streaming


๐Ÿ› ๏ธ Technology Stack & Expertise

๐ŸŽฏ Click to expand full tech stack

๐Ÿ’ป Programming Languages

๐Ÿค– AI/ML Frameworks & Deep Learning

๐Ÿ”ฅ LLM & Generative AI

๐Ÿ—„๏ธ Vector Databases & Embeddings

๐ŸŽฏ Specialized AI Domains

๐Ÿ“Š Data Engineering & Big Data

โ˜๏ธ Cloud & Infrastructure

๐Ÿ”ง MLOps & DevOps

๐Ÿ”ฌ ML Experiment Tracking & Optimization

๐Ÿ”ง Version Control & Collaboration

๐Ÿ—„๏ธ Databases & Data Warehousing

๐Ÿ“ˆ Data Visualization & BI

๐Ÿ“Š Monitoring & Observability

๐ŸŒ API & Communication

๐Ÿงช Testing & Quality Assurance

๐ŸŒ Web Development

๐Ÿ’ผ Professional Skills & Methodologies

๐Ÿ“š Research & Publications

๐Ÿ“– Published Research

  • ๐ŸŽ“ Multiple papers on Google Scholar
  • ๐Ÿ“Š Focus areas: Deep Learning, NLP, Computer Vision
  • ๐ŸŒ International conference presentations
  • ๐Ÿ“ Peer-reviewed journal publications

๐Ÿ“ฆ Open Source Contributions

  • ๐Ÿ PyPI Packages
  • โญ Active contributor to ML/AI projects
  • ๐Ÿ”ง Maintainer of data engineering tools
  • ๐ŸŒŸ Growing open-source community

๐Ÿ’ก Core Competencies

๐Ÿค– AI & Machine Learning

  • End-to-End Model Development: From ideation and data collection to model training, evaluation, and deployment.
  • Deep Learning Specialization: Expertise in building and optimizing neural networks for complex tasks.
  • NLP & Computer Vision: Proven experience in creating solutions for text analysis, image recognition, and object detection.
  • Model Optimization & Scaling: Techniques for improving model performance, reducing latency, and ensuring scalability.

๐Ÿ“Š Data Engineering & MLOps

  • Scalable Data Pipelines: Designing and implementing robust ETL and real-time streaming pipelines for large-scale data processing.
  • Cloud-Native MLOps: Automating the entire machine learning lifecycle with CI/CD, containerization, and infrastructure as code.
  • Big Data Technologies: Proficient in using distributed computing frameworks to handle massive datasets.
  • Monitoring & Observability: Implementing comprehensive monitoring and logging to ensure system reliability and performance.

๐Ÿš€ Product & Strategy

  • Technical Strategy & Vision: Aligning technology with business goals to drive innovation and create a competitive advantage.
  • Product-Oriented Development: Focusing on delivering tangible business value and a seamless user experience.
  • Agile Project Management: Leading projects with a focus on iterative development, collaboration, and on-time delivery.
  • Stakeholder Communication: Effectively communicating complex technical concepts to both technical and non-technical audiences.

๐Ÿค Leadership & Collaboration

  • Cross-Functional Team Leadership: Guiding and mentoring teams to foster a culture of innovation and excellence.
  • Open-Source Contribution: Actively contributing to the open-source community and promoting knowledge sharing.
  • Community Building: Engaging with the tech community through speaking, writing, and mentorship.
  • Client & Partner Engagement: Building strong relationships with clients and partners to ensure project success.

๐Ÿ“Š GitHub Analytics

GitHub Stats GitHub Streak

Top Languages Contribution Graph

Contribution Graph

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๐ŸŽฏ Currently

๐Ÿ”ญ Working On

  • Advanced NLP systems
  • Real-time ML pipelines
  • Scalable AI infrastructure
  • Computer Vision applications

๐ŸŒฑ Learning

  • Reinforcement Learning
  • LLM Fine-tuning
  • Edge AI Deployment
  • Quantum ML

๐Ÿค Open To

  • Full-time opportunities
  • Contract projects
  • Consulting engagements
  • Research collaborations

๐Ÿ† Achievements & Recognition

GitHub Trophies

๐ŸŽฏ Achievement ๐Ÿ“Š Metric
Production Models 10+ deployed
GitHub Stars Growing community
Open Source Packages 5+ on PyPI
Research Publications Multiple papers
Project Success Rate 95%+
Code Quality A+ rated

๐Ÿ’ผ Services I Offer

๐Ÿš€ For Companies

  • โœ… ML Model Development - Custom AI solutions
  • โœ… Data Pipeline Architecture - Scalable ETL systems
  • โœ… MLOps Implementation - End-to-end deployment
  • โœ… Technical Consultation - Strategy & architecture
  • โœ… Team Training - ML/AI workshops
  • โœ… Code Review & Optimization - Performance tuning

๐Ÿค For Startups & Investors

  • โœ… MVP Development - Rapid prototyping
  • โœ… Technical Due Diligence - AI/ML assessment
  • โœ… Proof of Concept - Feasibility studies
  • โœ… Architecture Design - Scalable foundations
  • โœ… Cost Optimization - Cloud & infrastructure
  • โœ… CTO Advisory - Strategic technical guidance

๐Ÿ“ž Let's Build Something Amazing Together!

๐Ÿš€ I'm actively seeking opportunities to create impact through AI & Machine Learning

LinkedIn Email Portfolio

๐Ÿ’ก "Turning complex data into actionable intelligence, one model at a time."


โšก Fun Facts About Me
  • ๐ŸŽจ Passionate about the intersection of technology and art
  • ๐Ÿ† Regular hackathon participant and winner
  • ๐Ÿ“š Avid reader of AI research papers and tech blogs
  • ๐ŸŒ Love exploring global tech communities
  • โ˜• Coffee enthusiast (fuel for coding marathons)
  • ๐ŸŽฎ Interested in AI for gaming and procedural generation
  • ๐ŸŽฏ Believer in clean code and elegant solutions
  • ๐ŸŒฑ Advocate for open-source and knowledge sharing

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โญ From karimosman89 - Let's innovate together!

Pinned Loading

  1. Time-Series-Forecasting Time-Series-Forecasting Public

    A collection of Jupyter Notebooks covering data wrangling, visualization, and machine learning algorithms.

    Jupyter Notebook 1

  2. X_Ray_Project X_Ray_Project Public

    A collection of Jupyter Notebooks covering data wrangling, visualization, and machine learning algorithms.

    Jupyter Notebook 1

  3. AI-Project AI-Project Public

    This project, you will build a full AI pipeline for an image classification task using Convolutional Neural Networks (CNNs). The project will cover data ingestion, preprocessing, model training, deโ€ฆ

    Python 2

  4. ab-testing ab-testing Public

    Analyzes the results of A/B tests to determine if there is a statistically significant difference between control and treatment groups. It provides a structured approach for performing A/B tests, โ€ฆ

    Python 1

  5. Data-Pipeline Data-Pipeline Public

    This project implements a scalable ETL pipeline that processes streaming data from Kafka and performs analytics using Spark.

    Python 1

  6. reinforcement-learning reinforcement-learning Public

    Create an agent that learns to play a game (e.g., Atari, chess) using reinforcement learning algorithms like Deep Q-Networks (DQN) or Proximal Policy Optimization (PPO).

    Python 1