Ten days into the journey, the excitement has yet to wear off. Everything looks shiny and new, and for me, every new (good) paper read is full of discovery and unspools new threads of thought. However, it is important that I keep myself grounded and on pace.
My scholars class has been given ample resources: mentorship, compute, repositories, texts and guidelines. Still, I expect this process to be windy from start to finish, perhaps looking like this:
stateDiagram [*] --> ExploreIdeas ExploreIdeas --> Pursue ExploreIdeas --> Discard Discard --> ExploreIdeas Pursue --> Experiment Experiment --> MinorSuccess Experiment --> Fail Experiment --> Breakthrough Fail --> ExploreIdeas MinorSuccess --> Experiment Breakthrough --> ProbeDiscuss ProbeDiscuss --> Project Project --> [*]
My plan, therefore, is to plan for flexibility. While my mentor and I have made a schedule for my learning, it is up to change, subject to new ideas and findings. Nevertheless, here is a rough idea of what I will be aiming for:
gantt section Gantt Compute set-up :done, des1, 2020-10-12,2020-10-23 ResNet in PyTorch :active, des2, 2020-10-16, 14d Language Model in PyTorch: des3, after des1, 14d OpenAI Gym Expts: des4, after des2, 4d Readings and Study Group: active, des5, after des1, 30d Data Experiments: des6, after des2, 21d Research Plan: des7, 2020-11-15,2020-11-30 Research Project: des8, 2020-12-01-2021-04-01 Presentation: des9, after des8
I am thankful for the
My technical set-up is relatively simple, and has involved:
- Set up Microsoft VM according to desired specs
- Generate SSH keys for access via terminal tunnel
- Install desired packages
- Enable Jupyter notebook to run remotely on VM, via port forwarding
- As best practice, when trying to work with specific tutorials where one can anticipate package version conflicts, work within virtual environments
For the next few weeks, I plan to complete the first 3 experiments I have in mind, and be on strong enough footing to pursue one or two passable ideas. See you then.