Python developer | AI & Mechatronics engineer
I design smart automation systems and AI solutions to enhance industrial efficiency and manufacturing performance.
I enjoy solving real-world engineering challenges by combining data-driven intelligence with practical automation techniques. My work focuses on improving processes, reducing downtime, and increasing productivity through innovative technology. I’m passionate about Industry 4.0, predictive maintenance, and creating systems that make factories smarter and more sustainable.
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Real-world projects using Python, scikit-learn, TensorFlow, and PyTorch
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Classification, regression, and predictive models
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Time-series analysis and anomaly detection
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Q-learning projects and simulations
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Intelligent agents for decision-making
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Automation projects for industrial systems
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Industrial automation examples and practical case studies
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Mechanical design and system integration
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Manufacturing process improvement projects
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Data cleaning, visualization, and reporting
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Advanced Excel and data-driven decision making
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Insights and performance analysis
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Contributions to open-source projects
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Team collaborations on real engineering challenges
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Shared resources, tutorials, and learning notes
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My progress in AI and Industry 4.0
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New tools and technologies I’m learning
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Notes and mini-projects for personal growth
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Python
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C / C++
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MATLAB
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Machine Learning (scikit-learn)
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Deep Learning (TensorFlow / PyTorch)
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Reinforcement Learning (Q-learning, etc.)
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Data analysis & visualization
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PLC basics
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Industrial automation
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Sensors & actuators
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Mechanical design & manufacturing
- Git & GitHub — Version control, collaboration, and open-source
- Jupyter Notebook — Data analysis, experimentation, and reporting
- VS Code — Development environment and debugging
- PyCharm — Python development and project management
- MATLAB & Simulink — Modeling, simulation, and control systems
- Excel (Advanced) — Data processing, dashboards, and reporting
- Pygame — Game development and visualization projects
- Google Colab — Cloud-based experiments and model training
- AI & automation for industrial systems
- Generalizing diagnosis models for broader applications.
- Spreading know-how and promoting digital transformation in the industrial sector through AI.
- Predictive maintenance and data-driven optimization
- Building practical, real-world engineering projects
- Predictive Maintenance using vibration data and machine learning
- Reinforcement Learning projects
- Automation projects for industrial processes
- Anomaly Detection: Unsupervised and semi-supervised method for the anomaly detection of industrial machinery.
- LLMs for machine diagnosis and maintenance: Bridging diagnosis and maintenance workflows with LLMs capabilites through Model Context Protocol.
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AI projects related to Industry 4.0
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Robotics & automation systems
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Data science projects (classification, anomaly detection, time-series)
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Open-source projects in Python / AI / Mechatronics
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Python programming and automation
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AI & Machine Learning projects
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Reinforcement Learning (Q-learning)
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Industrial engineering & mechatronics
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Predictive maintenance and data analysis
You can reach me here or through my GitHub profile.
Email: khadibd00@gmail.com