Machine Learning (ML)
- In research and development, there is a sense of complex about not using advanced techniques such as Machine Learning and Deep Learning.
- There is a feeling that most people have not done anything more advanced than “using AI services or models provided by APIs” (blu3mo).
- However, this might just be due to an outdated image of high barriers set during high school.
- I was just starting to learn calculus, let alone linear algebra.
- I struggled a lot in the Master of Information Science program, which may have created an image in my mind that certain things are difficult for me.
- Now, there is a possibility that I could do some of those advanced things.
- I have taken courses like Linear Algebra, AI (COMSW4701), and Computational Aspects of Robotics COMS W4733.
- Thanks to that, I am becoming less intimidated by formulas involving calculus and matrices.
- I am starting to understand how to read research papers.
- In fact, I learned about the workings of Neural Networks in Tokyo University 1S Information α, and even played around with CNNs and GANs.
- I have taken courses like Linear Algebra, AI (COMSW4701), and Computational Aspects of Robotics COMS W4733.
- Goals
- To gain a correct understanding of “what I can and cannot do.”
- This will increase the things I recognize as “things I can do,” which makes me happy.
- To gain a correct understanding of “what I can and cannot do.”
- Things I can do
- Read interesting papers that use known ML techniques with enthusiasm.
- In the field of HCI, this is often not considered core, so I have tended to skim through them based on the atmosphere.
- There is a theory that if I try to read them properly, I can understand them.
- I also want to try implementing them myself.
- Ideas that come to mind
- Placement Retargeting of Virtual Avatars to Dissimilar Indoor Environments
- Researchers combining ML and HCI
- In the field of HCI, this is often not considered core, so I have tended to skim through them based on the atmosphere.
- Read famous papers.
- I want to understand at least Transformer, GPT, and Diffusion Model.
- I think these areas have well-established highways of knowledge.
- I want to understand at least Transformer, GPT, and Diffusion Model.
- Engage in hands-on activities.
- Rather than “building LLAMA/GPT from scratch,” I want to do more practical tasks to understand the extent of what I can do.
- Read interesting papers that use known ML techniques with enthusiasm.