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About
Backbone.js gives structure to web applications by providing models with key-value binding and custom events, collections with a rich API of enumerable functions, views with declarative event handling, and connects it all to your existing API over a RESTful JSON interface. When working on a web application that involves a lot of JavaScript, one of the first things you learn is to stop tying your data to the DOM. It's all too easy to create JavaScript applications that end up as tangled piles of jQuery selectors and callbacks, all trying frantically to keep data in sync between the HTML UI, your JavaScript logic, and the database on your server. For rich client-side applications, a more structured approach is often helpful. With Backbone, you represent your data as Models, which can be created, validated, destroyed, and saved to the server.
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About
jQuery is a fast, small, and feature-rich JavaScript library. It makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers. If you're new to jQuery. Return a collection of matched elements either found in the DOM based on passed argument(s) or created by passing an HTML string. All the aspects of the API that were deprecated in the corresponding version of jQuery. These methods get and set DOM attributes of elements.
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About
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
JavaScript Library solution for developers
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Audience
JavaScript Library solution for developers
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Audience
Users and anyone in search of a solution to calculate the estimation of many different statistical models
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationBackbone.js
backbonejs.org
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Company InformationjQuery
jquery.com
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Company Informationstatsmodels
www.statsmodels.org/stable/index.html
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Alternatives |
Alternatives |
Alternatives |
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Categories |
Categories |
Categories |
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Integrations
CodeLobster IDE
CodeRush
CoreIDE
Froala
LuGo-Test
MERCI Cloud ERP
NSwag
PhantomJS
Popper
RadSystems
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Integrations
CodeLobster IDE
CodeRush
CoreIDE
Froala
LuGo-Test
MERCI Cloud ERP
NSwag
PhantomJS
Popper
RadSystems
|
Integrations
CodeLobster IDE
CodeRush
CoreIDE
Froala
LuGo-Test
MERCI Cloud ERP
NSwag
PhantomJS
Popper
RadSystems
|
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