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Hi There 👋

I'm Mo, a passionate data enthusiast interested in Business Analytics, Statistical Analysis, and Machine Learning.

My background includes developing and implementing machine learning models, leveraging statistical analysis for meaningful interpretations, and optimizing processes to drive business efficiency.

In addition to my practical experience, I've designed and developed a comprehensive Machine Learning course. Teaching is my way of contributing to the community and spreading knowledge about the fascinating world of ML.

Interests and expertise

  • 👀 Business Analytics: Uncovering patterns and trends in data to inform strategic decision-making.
  • 📈 Statistical Analysis: Applying statistical techniques to gain insights and make data-driven decisions.
  • 🧐 Machine Learning: Developing and deploying ML models for predictive analysis and pattern recognition.
  • 🎯 Optimization: Passionate about optimization techniques and their applications in solving real-world problems.

Current Projects

🔍 I'm currently working on completing my machine learning course codes and course scheduling optimization problem. Excited to collaborate and share ideas with the GitHub community.

Courses

📚 Check out my Machine Learning Course, where I cover fundamental concepts and practical applications to help learners dive into the ML world.

Let's Connect!

🌐 Explore my repositories for projects, code snippets, and more. Connect with me on LinkedIn, and let's discuss all the data!

Thanks!

Mohammad Rahdar

Mo Rahdar's Projects

cutting-stock-optimization icon cutting-stock-optimization

The cutting-stock problem is a challenge encountered in manufacturing and production optimization. This problem involves the efficient cutting of standard-sized pieces of stock material, such as paper rolls or sheet metal, into smaller pieces of specified sizes. The primary objective is to minimize material waste during the cutting process.

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