MLJ.jl
Vapor
MLJ.jl | Vapor | |
---|---|---|
6 | 57 | |
1,725 | 23,810 | |
0.6% | 0.4% | |
8.7 | 8.3 | |
1 day ago | 4 days ago | |
Julia | Swift | |
GNU General Public License v3.0 or later | MIT License |
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MLJ.jl
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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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My experience working as a technical writer for MLJ
MLJ is a machine learning framework for Julia, which you can kind of infer from the article but it's not super obvious IMO.
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[N] New BetaML v0.8: model definition, hyperparameters tuning and fitting in 2 lines
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, with a detailed tutorial on its usage from Python or R (no wrapper packages are needed) and an extensive interface to MLJ.
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Python vs Julia
You should definitely go with Julia. It has steeper learning curve than python, but it is way more powerful. As for the ecosystem, you shouldn't worry about that much: DataFrames.jl and friends is way better than pandas, MLJ.jl (https://github.com/alan-turing-institute/MLJ.jl) and FastAI.jl(https://github.com/FluxML/FastAI.jl) are great frameworks for regular ML and deepnet. And if at any point you get a feeling that you need some python library, you can always plug it in with PyCall.jl(https://github.com/JuliaPy/PyCall.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.
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Swift for TensorFlow Shuts Down
Then you haven't looked at Julia's ecosystem.
It may not be quite as mature, but it's getting there quickly.
It's also far more interoperable because of Julia's multiple dispatch and abstract types.
For example, the https://github.com/alan-turing-institute/MLJ.jl ML framework (sklearn on steroids), works with any table object that implements the Tables.jl interface out of the box, not just with dataframes.
That's just one example.
Vapor
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Swiftly Chatting: Building Chatbots with Botter
Botter works in tandem with Vapor, which handles the server-side functions of your project. This powerful combination allows you to focus on what matters most - creating an engaging and effective chatbot.
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Issue with Vapor Server
// swift-tools-version: 5.8 // The swift-tools-version declares the minimum version of Swift required to build this package. import PackageDescription let package = Package( name: "MyServer", platforms: [.macOS("12.0")], products: [ // Products define the executables and libraries a package produces, and make them visible to other packages. .executable( name: "MyServer", targets: ["MyServer"]), ], dependencies: [ .package(url: "https://github.com/vapor/vapor.git", .upToNextMajor(from: "4.70.0")), // Dependencies declare other packages that this package depends on. // .package(url: /* package url */, from: "1.0.0"), ], targets: [ // Targets are the basic building blocks of a package. A target can define a module or a test suite. // Targets can depend on other targets in this package, and on products in packages this package depends on. .executableTarget( name: "MyServer", dependencies: [ .product(name: "Vapor", package: "vapor") ]), .testTarget( name: "MyServerTests", dependencies: ["MyServer"]), ] )
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Is it possible/straightforward to have a webserver baked in to an iOS app?
Otherwise there's https://github.com/vapor/vapor
- A Look at the Crystal Programming Language for Humans
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Most effective approach for building a client/server application (MacOS)
The Swift/Vapor project is a relatively easy way to do it.
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First contract, how much should I charge?
Opening this webpage (https://vapor.codes) cranks my CPU (5800x3d) to 100% instantly. Why?
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Swift outside the Apple ecosystem
Vapor is the most popular non-Apple-ecosystem Swift project. There have been a few others, but none particularly popular.
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Idea for small project? (without touching any UI)
Server-side apps (typically via Vapor)
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Why I selected Elixir and Phoenix as my main stack
My first option other than PHP was using Swift and Vapor. I have made some projects with iOS and Objective-C, maybe I could also learn Swift and create both native iOS apps and backends with the same language.
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I've just released my new app which allows you to use your iPhone as a webcam when livestreaming
StreamCam is written 100% in Swift, SwiftUI & Combine. The serverside is handled with Vapor.
What are some alternatives?
ScikitLearn.jl - Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/
Perfect - Server-side Swift. The Perfect core toolset and framework for Swift Developers. (For mobile back-end development, website and API development, and more…)
AutoMLPipeline.jl - A package that makes it trivial to create and evaluate machine learning pipeline architectures.
Alamofire - Elegant HTTP Networking in Swift
Enzyme.jl - Julia bindings for the Enzyme automatic differentiator
Kitura - A Swift web framework and HTTP server.
PythonNet - Python for .NET is a package that gives Python programmers nearly seamless integration with the .NET Common Language Runtime (CLR) and provides a powerful application scripting tool for .NET developers.
hummingbird - Lightweight, flexible HTTP server framework written in Swift
Distributions.jl - A Julia package for probability distributions and associated functions.
swifter - Tiny http server engine written in Swift programming language.
pyTsetlinMachine - Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
GCDWebServer - The #1 HTTP server for iOS, macOS & tvOS (also includes web based uploader & WebDAV server)