Package: tglcourse
The Generative LandscapeThis is still a work in progress, but most of the important bits should
be done in time for a launch on Friday, Novermer 25! In the meantime,
you can check out myprevious course,
AIAIARTor join the Discord
where I’ll be streaming final lesson checks and updates.If you want to support this effort, I now have a Patreon:https://www.patreon.com/johnowhitakerThe material will show in github pages athttps://johnowhitaker.github.io/tglcourse/(and thehttp://thegenerativelandscape.comwill redirect there now too). Hooray
for the magic of nbdev.Join ourDiscordto discuss the course,
join study groups or chat about all things generative. That’s also the
place to go for notifications of live lesson walkthroughs and course
updates.Check out theGetting Startedpage for an
overview of the course and more information on things like study
groups.Check out theLibrarypage
for information on thetglcourselibrary that accompanies the course.The PlanThe idea is to have a core curriculum building up to an understanding of
key generative modelling techniques, split into three rough sections.
The first 5 lessons will cover basics of building NNs and crafting loss
functions. Lessons 6-10 will introduce generative modelling, GANs and
working with sequences using transformers. Lessons 11-15 will be a deep
dive into diffusion models, and lesson 16 will wrap up and give
sugestions for new directions to explore.Alongside this will be a number of ‘bonus’ notebooks that don’t need to
be completed but which augment the core content. Managing datasets,
experiment tracking, sharing demos and so on. Some will augment specific
lessons, some will add functionality to the library and some will just
be standalone topics I think are cool. The latter category is likely to
continue to grow even after the course launches :)There will be three suggested projects (after lessons 5, 11 and 14) to
mark milestones in the course, and the final lesson will also encourage
you to do a larger project at the end. Once we launch there’ll be a
place to everyone’s projects and some prizes for the best.This table has a rough status on the main lessons.LessonDescriptionStatusLesson 1: PyTorch BasicsIntro to PT, tensor manipulation, images as tensors, LeastAverageImage exerciseDoneLesson 2: OptimizationIntro to GD, optimization examples exerciseRough Draft DoneLesson 3: Building NNsnn.Module, building blocks, CNNsRough Draft DoneLesson 4: Learning RepresentationsWhat do networks learn, style transferWIPLesson 5: CLIPDemo use as a loss function, video deep dive into VQGAN notebooksRough Draft DoneLesson 6: Generative ModellingVAE part, latent walks, PCAWIPLesson 7: GANs 1Intro to GANs, DC GAN, ConditioningWIPLesson 8: GANs 2GAN training tricks, NOGAN, using modern GANs, VQGANNot StartedLesson 9: Sequence Modelling Introidea, language modelling concept, transformer demoWIPLesson 10: TransformersIntro to transformes, attention, comparing to lstm, reading minGPTNot StartedLesson 11: Everythign is a sequenceShow whistlegen, protein, VQGAN, parti…Not StartedLesson 12: DM 1Intro to diffusion models, toy example, comparison to DDPMRough Draft DoneLesson 13: DM2Conditioning, CFG, guiding, sampling, better trainingWIPLesson 14: DM3SD deep diveRough Draft DoneLesson 15: DM4Other modalities - ideally demo class-conditioned audio generation. Might not be done by the time the course launches but would be nice to have.WIPLesson 16: Going FurtherFinding your niche, exploring less common areasWIPFAQsSome course-related questions that have tricked in:+ ‘Any
prerequisites?’: If you’re comfortable with a bit of Python and using
Jupyter Notebooks you should be ready to take this course. No prior deep
learning knowledge is assumed, and although we will dive fairly deep
fairly quickly I’ve tried to link lots of resources wherever possible.+ ‘How long is the course?’: There are 15 core lessons plus a
number of bonus notebooks. You can take them at whatever pace you find
enjoyable, or join in with a study group on Discord to work through one
a week.+ ‘Does the HuggingFace Diffusion Model Class supercede
this?’: I’ve teamed up with HF to help build theirdiffusion model
class, sharing a
lot of material between it and this course. Both will have unique things
to add - I’d recommend signing up for theirs even if you’re working
through ‘The Generative Landscape’ as well, since there will be extra
projects and fun community activities to get involved in with that one
too.+ ‘Can genereative landscape be real?’: Yes, if you subscribe
toDavid Chalmers ‘simulation
realism’;)+ ‘Will it include stable diffusion?’: Yes, see lesson 14+
‘Will we learn how to adapt these method to 3d?’: At some point I’d love
to add more 3D related content - stay tuned for bonus notebooks once the
craziness of the course launch calms down.+ ‘I hope this includes
generating text!’: It does! Lessons 9 - 11 deal with modelling
sequences, and should set you up with everything you need to make models
which can spew out AI-generated gibberish all day long.+‘My
question isn’t in the FAQs?’: OK, so I made this one up. But if you have
a burning question, send it to me and I’ll add it here.CI status:Page stats: Total Hits:Page visitors: