julia_titanic_model
Titanic machine learning model and web service (by AndreyGermanov)
ScikitLearn.jl
Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/ (by cstjean)
julia_titanic_model | ScikitLearn.jl | |
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1 | 4 | |
3 | 540 | |
- | - | |
0.0 | 3.9 | |
about 1 year ago | 11 months ago | |
Jupyter Notebook | Julia | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
julia_titanic_model
Posts with mentions or reviews of julia_titanic_model.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-17.
ScikitLearn.jl
Posts with mentions or reviews of ScikitLearn.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-17.
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Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
For machine learning, we will use SciKitLearn.jl library, which replicates SciKit-Learn library for Python. It provides an interface for commonly used machine learning models like Logistic Regression, Decission Tree or Random Forest. SciKitLearn.jl is not a single package but a rich ecosystem with many packages, and you need to select which of them to install and import. You can find a list of supported models here. Some of them are built-in Julia models, others are imported from Python. Also, the SciKitLearn.jl has a lot of tools to tune the learning process and evaluate results.
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What is the Julia equivalent of Scikit-Learn?
MLJ.jl is a good Julia ML framework. There's also a Scikitlearn.jl but its more of a wrapper around the sklearn I believe
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Fit_transform not defined
That repo appears to be deprecated. Since you called using ScikitLearn, I imagine you should check this repo instead: https://github.com/cstjean/ScikitLearn.jl
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sklearn equivalent for Julia?
Imho, Julia is more diverse in the sense that there is not a single popular ML library. Maybe the Julian equivalent for scikit-learn is MLJ.jl. There is also ScikitLearn.jl, which defines the usual interface of scikit-learn models, and specific algorithms then implement this interface.
What are some alternatives?
When comparing julia_titanic_model and ScikitLearn.jl you can also consider the following projects:
PlotDocs.jl - Documentation for Plots.jl
MLJ.jl - A Julia machine learning framework
DataScience - Data Science in Julia course for JuliaAcademy.com, taught by Huda Nassar
BeautifulAlgorithms.jl - Concise and beautiful algorithms written in Julia
NumPy - The fundamental package for scientific computing with Python.
DataFrames.jl - In-memory tabular data in Julia
cheatsheets - Official Matplotlib cheat sheets
LIBSVM.jl - LIBSVM bindings for Julia
JLD2.jl - HDF5-compatible file format in pure Julia
julia - The Julia Programming Language
HTTP.jl - HTTP for Julia
julia_titanic_model vs PlotDocs.jl
ScikitLearn.jl vs MLJ.jl
julia_titanic_model vs DataScience
ScikitLearn.jl vs BeautifulAlgorithms.jl
julia_titanic_model vs NumPy
ScikitLearn.jl vs DataFrames.jl
julia_titanic_model vs cheatsheets
ScikitLearn.jl vs LIBSVM.jl
julia_titanic_model vs JLD2.jl
ScikitLearn.jl vs julia
julia_titanic_model vs HTTP.jl
ScikitLearn.jl vs DataScience