Comments (4)
Design decisions to discuss:
- Data container (agnostic to specifics)
- Task descriptions / Composition
- Meta-learning (hyperparameter setting)
- Model composition
- Evaluation and diagnostics (simple set of available metrics, benchmarks, diagnostics plots)
from mlj.jl.
See the poster for a bit more details: https://github.com/alan-turing-institute/mlj/blob/master/material/MLJ-JuliaCon2018-poster.pdf
from mlj.jl.
Design decisions to discuss:
- Data container (agnostic to specifics)
- Task descriptions / Composition
- Meta-learning (hyperparameter setting)
- Model composition
- Evaluation and diagnostics (simple set of available metrics, benchmarks, diagnostics plots)
I think each of these deserves an issue otherwise it's going to be a bit of a mess on a single thread. We can also better set priority being set as independent
from mlj.jl.
Agenda for Machine Learning in Julia Kickoff meeting
-
introductions; expressions of special interests within the project
-
clarify the status of the mlj repo: what bits of code are known to be broken, etc
-
to further that end, make a plan for getting some basic test
code into "runtests.jl", and setting up Travis -
clarification of protocols and responsibility for managing the repo
-
determine if there are any known obstacles to moving to Julia 0.7
-
field feedback on Anthony's proposal for the package interface spec.
-
draw up a list of other immediate priorities and tasks and,
determine who will take responsibility for what. -
time permitting, a discussion of some intermediate-level design aspects:
-
lazy loading versus automatic loading of packages/interfaces
-
learning networks (aka pipelines, composite learners)
-
agnostic data containers
Please take a look at this idea for conceptualization learning networks as "dynamic data" and this suggestion for supporting multiple data containers. Both suggestions
are implemented in this proof-of-concept repo. -
Anyone want to add something?
from mlj.jl.
Related Issues (20)
- SymbolicRegression.jl — registry update HOT 2
- Is the Averager documentation deprecated? HOT 2
- Update deprecated document example in "Transformers ..." section of manual
- `fit!` not exported in 0.19.3/0.19.4? HOT 2
- is there support for segmented or nested models? HOT 1
- Doc generation is failing silently HOT 2
- A de-correlation model for feature exclusion HOT 1
- [Tracking] Migration of measures MLJBase.jl -> StatisticalMeasures.jl HOT 1
- Add more examples of exported learning networks
- Confusing Julia code in adding_models_for_general_use.md HOT 1
- Include MLJBalancing.jl in MLJ and re-export it's names.
- Update docs for new class imbalance support
- Add new sk-learn models to the docs
- Export the name `MLJFlow` HOT 1
- `evaluate` errors HOT 3
- Add AutoEncoderMLJ model (part of BetaML) HOT 10
- need a tutorial for using logger with dagshub and mlflow HOT 4
- Document how to add plot recipes in a new model implementation HOT 4
- Add new model descriptors to fix doc-generation fail HOT 1
- Two models fail integration tests but defy isolation
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from mlj.jl.