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Here are my recent top tools and techniques π οΈ used to tackle complex projects in Machine Learning π€ and Computer Vision ποΈ:
- Frameworks: ποΈ TensorFlow, π₯ PyTorch, π§ Scikit-learn
- Optimization: π TensorRT, π ONNX
- Data Processing: π NumPy, π Pandas
- Visualization: π Matplotlib, π Plotly
- Model Deployment: π₯οΈ TensorFlow, π Flask, β‘ FastAPI
- Cloud Platforms: βοΈ Google Cloud AI
- Version Control: π·οΈ MLflow, π Weights & Biases
- π’ Image Processing: π· OpenCV
- π‘ Object Detection: π― YOLO, β‘ Faster R-CNN, ποΈ SSD
- π΄ Segmentation: π Mask R-CNN
- π£ Pose Estimation: π OpenPose, β MediaPipe
- π΅ 3D Vision: π οΈ Open3D
- π Augmentation: π torchvision.transforms
Also exploring:
Python |
Pytorch |
NumPy |
GCP |
![]() TensorRT |
![]() OpenCV |
Jupyter |
Nvidia |
![]() Blender |
Ubuntu |
Here's the tech stack I work with daily:
HTML |
CSS |
Bootstrap |
DevTools |
Python |
Flask |
JavaScript |
GCP |
Recent areas of exploration:
ROS/ROS2 |
![]() Microcontrollers |
![]() Embedded |
Python |
Docker |
Grafana |
Ubuntu |
![]() Bash |
- π Portfolio Website
- π§ Email
- πΌ LinkedIn
Piotr Gapski Β© 2025 | Machine Learning & Computer Vision Engineer | Open to new Opportunities!