On October 8-9, I attended the "From Scratch Diffusion Coding" training, which provided a rich experience both theoretically and practically. I learned the fundamental principles of diffusion models and got acquainted with advanced techniques like inpainting. Additionally, I deepened my interest in software and coding, solidifying my goals of specializing in this field.
History and Fundamentals of Coding
In the initial stages of the training, detailed information was provided about the history and fundamental principles of coding. Gaining a broad perspective on the evolution of programming languages and the modern software world helped me better understand the significant role coding plays in technology.
Diffusion Models: Fundamental Principles
Diffusion models are important tools in the world of artificial intelligence and image processing. During the training, we learned about the working principles of these models and carried out practical applications. The opportunities they presented for image generation and manipulation had great potential for creative projects.
What is Inpainting and Our Works on Izmir Images
Inpainting is a technique aimed at filling in missing or damaged areas of an image using artificial intelligence. During the training, we worked on inpainting projects using images of İzmir. These projects involved applying this technique to the city's historical structures and landscapes, effectively completing the missing parts of the images with diffusion models. This process was both technically and aesthetically educational.
Prompt Writing and Fundamental Principles of Coding
Correct "prompt writing" was critical for effectively guiding the outputs generated by the model. I had the opportunity to gain in-depth knowledge in this area during the training. Furthermore, we focused on the fundamental principles of coding, learning how to effectively utilize algorithms when working with artificial intelligence models.
Working Experience with Google Colaboratory
During the training, we used the Google Colaboratory (Colab) platform to conduct cloud-based artificial intelligence projects. The GPU acceleration options provided by Colab allowed us to work more efficiently on large datasets and diffusion models. While practicing coding on Colab, I gained important skills in integrating and editing artificial intelligence models.
Future Goals
This training allowed me to deepen my interest in software and coding. I aspire to specialize in this field in the future, and techniques like diffusion models and inpainting have provided an essential starting point for my coding career.
Acknowledgments
The workshop was held at the Izmir Chamber of Architects. I would like to sincerely thank Kaan Bingöl, Sadık Aksu, Gizem Mersin, and Lale Başarır, a member of the Izmir Chamber of Architects' Branch Management Board, for their efforts and guidance throughout this process. Their contributions significantly enhanced my technical knowledge and experience.
Conclusion
These two days of training were incredibly valuable for me in terms of both technical knowledge and practical experience. The step I took in the world of coding and artificial intelligence has created an important foundation for my future projects.
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