Gincker Platform

Gincker Platform provides the same development environment to both developers and users. It converts different applications into templates, and it implements a common interface and standardized input/output format by encapsulating and centralizing all the programming and implementation details internally. As long as you work through one template, you will be able to use all the other templates. You can simply go to gincker.com, select a proper playground and template, and create your desired application out of the box.

The Gincker Platform allows you to save your work to gincker that is a unique URL link. The saved gincker can not only provide output results, but also bring the development environment directly to users. Users can then use the gincker to regenerate, manipulate, modify, and customize graphics, machine-learning algorithms, or trading strategies.

Currently, Gincker Platform implements 4 playgrounds: Graphics, Machine Learning, Books, and Finance.

You can go to Gincker Home by clicking on this button: Gincker Home

Create charts and graphics without code

Graphics Playground

With Gincker Graphics Playground, you can create advanced charts and graphics for any mathematic function or data without the need of writing a single line code.

Gincker Graphics Playground includes a variety types of charts and graphics, including 2D charts, 3D charts and graphics, complex-variable charts, and vector charts. It makes chart and graphics creation as easy as using a calculator, and it also makes graphics delivery and sharing over the internet as simple as posting a Tweet.

Gincker Graphics also implements a powerful math parser that allows you to create charts and graphics by entering standard math formulas with various parameters. For example, the formula sin(sqrt(x^2 + y^2))/sqrt(x^2 + y^2) will generate a 3D sinc chart.

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Create and test machine-learning algorithms

AI Playground

With Gincker AI Playground, you can create and test machine-learning (ML) algorithms without code. You can train machine-learning models with your own data and visualize ML results in real-time.

Gincker AI Playground implements various traditional ML models for classification and regression, as well as the deep-learning algorithms such as neural network for self-organizing map and time series. It also includes popular pretrained ML models for image classification, pose detection, face recognition, sentiment, and GPT-2 text generator.

It also includes several models for transfer learning that is a ML method where a pretrained model is reused as the starting point for training a new ML model. Transfer learning on Gincker AI Playground can greatly speed up the time it takes to develop and train a ML model.

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Technical Analysis in Quantitative Finance

Gincker Finance

With Gincker Finance, you can access to market data API, perform technical analysis, backtest trading strategies, and price for different asset types using various pricing engines.

Gincker Finance is a powerful technical analysis tool for individual traders and investors. It includes various free market data APIs, stock charts, over 50 technical indicators, over 30 predefined trading strategies, and an easy-to-use backtesting system. It also consists of a variety of pricing engines for evaluating equity options and fixed income instruments. Gincker Finance allows you to perform various technical analysis in quantitative finance.

Unlike traditional financial tools that require complicated programming and market data management, with Gincker Finance, you simply select a template, enter a stock ticker, specify corresponding parameters, and click on the "Run" button. The playground will automatically generate results on your screen.

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Books on graphics, finance, machine learning...

Gincker Books

The practical series books emphasize practical usefulness for real-world applications and provide the depth of information and level of detail. The books include ready-to-run example programs that allow you to explore the programming technique and algrithm behind the business applications. Some of the code examples are sophisticated packages for real-world applications. You can modify the code examples or add new features to them to form the basis of your own projects.

The books cover several specialized areas, including chart and graphics, AI and machine-learning, quantitative analysis and development for finacial market, numerical methods and math libraries, database development, etc. His recent book about charts and graphics with ASP.NET Core MVC covers advanced topics on cross-platform chart and graphics programming for real-world Web applications using C#, ASP.NET Core MVC, and JavaScript.

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