Racket

Racket

Racket Language
+

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About

BASIC (Beginners' All-purpose Symbolic Instruction Code) is a family of general-purpose, high-level programming languages designed for ease of use. Initially, BASIC concentrated on supporting straightforward mathematical work, with matrix arithmetic support from its initial implementation as a batch language, and character string functionality being added by 1965. The emergence of BASIC took place as part of a wider movement towards time-sharing systems. Some dialects of BASIC supported matrices and matrix operations, which can be used to solve sets of simultaneous linear algebraic equations. These dialects would directly support matrix operations such as assignment, addition, multiplication (of compatible matrix types), and evaluation of a determinant. BASIC declined in popularity in the 1990s, as more powerful microcomputers came to market and programming languages with advanced features (such as Pascal and C) became tenable on such computers.

About

Racket is a general-purpose, multi-paradigm programming language that serves as a modern dialect of Lisp and a descendant of Scheme. It is designed as a platform for programming language design and implementation, enabling developers to create new domain-specific and general-purpose languages. Racket's core language includes features such as macros, modules, lexical closures, tail calls, delimited continuations, parameters (fluid variables), software contracts, green threads, and OS threads. The language also comes with primitives, such as event spaces and custodians, which control resource management and enable the language to act like an operating system for loading and managing other programs. Further extensions to the language are created with the powerful macro system, which, together with the module system and custom parsers, can control all aspects of a language. Most language constructs in Racket are implemented as macros in the base language.

About

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone requiring an easy to use Programming Language

Audience

Programmers and educators looking for a programming language to improve scripting and computer science education

Audience

Engineers and data scientists requiring a solution to manage and improve their machine learning research

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

BASIC
United States
en.wikipedia.org/wiki/BASIC

Company Information

Racket Language
United States
racket-lang.org

Company Information

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Oxygene

Oxygene

RemObjects Software

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
Racket

Racket

Racket Language
ML.NET

ML.NET

Microsoft
MLlib

MLlib

Apache Software Foundation
Oxygene

Oxygene

RemObjects Software
Zig

Zig

Zig Software Foundation
Keepsake

Keepsake

Replicate

Categories

Categories

Categories

Integrations

BBEdit
CodePal
DagsHub
Databricks Data Intelligence Platform
Eclipse IDE
Emacs
Flower
Geany
Guild AI
Jupyter Notebook
Kate
Matplotlib
ModelOp
Neovim
Notepad++
NumPy
Python
Scheme
Vim
Visual Studio Code

Integrations

BBEdit
CodePal
DagsHub
Databricks Data Intelligence Platform
Eclipse IDE
Emacs
Flower
Geany
Guild AI
Jupyter Notebook
Kate
Matplotlib
ModelOp
Neovim
Notepad++
NumPy
Python
Scheme
Vim
Visual Studio Code

Integrations

BBEdit
CodePal
DagsHub
Databricks Data Intelligence Platform
Eclipse IDE
Emacs
Flower
Geany
Guild AI
Jupyter Notebook
Kate
Matplotlib
ModelOp
Neovim
Notepad++
NumPy
Python
Scheme
Vim
Visual Studio Code
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