palashio / nylon Goto Github PK

View Code? Open in Web Editor NEW

84.0 7.0 8.0 1.94 MB

An intelligent, flexible grammar of machine learning.

Home Page: http://docs.paraglide.ai

License: MIT License

Python 100.00%

machine-learning auto-ml grammar data-science

nylon's People

Contributors

Stargazers

Watchers

Forkers

adbmd schots rhythm99 akshayakula ruch-code sarda-devesh admariner bryan2022

nylon's Issues

should we get into graphs for statistics

should we get into confusion matrices etc. maybe possible integration with vega-lite

move analysis code into analysis.py

how to fetch standard workflows?

create a seperate module to help get standard specifications files to use

create design for correlations

things that users choose should affect the automatic choices in different parts of the pipeline. for example, if you add a trimming statement, more models should be tried out or a certain preprocessing mechanic should trigger certain models etc.

passing dictionary instead of json file

docker image for nylon

store this under a docker folder, check out github.com/palashio/libra for an example docker setup

uuid only generates when you run the model once, doesn't generate everytime there's a new run

class fields aren't being stored properly like json_file

adding bag of words type sparse model NLP

add documentation to the codebase

inference needs to work!!

get 5 people to review library before making it public

create demo gif

implement grid search / randomized search addition in modeling

add test cases for every possible type of addition/removal

y is being saved as None in models.history

model is saved as class str for some reason

calling something like

print(type(nylon_object.history['f16a0a8b-0c56-41c5-8c06-f6164c3b9095']['model'])) return a string

seperate code into individual functions etc.

overhaul documentation

check comment on reddit where lots of people agreed:

"It seems to be something useful. I wish the documentation was better. Before going into "how" it should first explain the "what". I've spent full 5 minutes skimming the github and the docs and I still don't know what this is.

"Nylon offers an easy to-use Python library to help users build complex machine learning models with the english language"

Is it a natural language processing framework? Or is it a framework with which I can build "complex machine learning models" just by describing them in plain English?

What is this?"

default modeling should try all the models without any parameters, and then find best parameters for that individual model

nylon_object = Polymer('housing.csv')

spec = {
    "data": {
        "target": "ocean_proximity"
    },
    "modeling": {
        "type": "svms"
    }
}

nylon_object.run(spec)