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What is Neuri?

We are engaged in cutting-edge research focused on artificial intelligence to gain significant advantages in the realm of financial investments, utilizing innovative neuro-prediction techniques to illuminate market dynamics. Our methodology incorporates sophisticated deep reinforcement learning algorithms and graph-based learning methodologies, along with artificial neural networks, to adeptly model and predict time series data. At Neuri, we prioritize the creation of synthetic datasets that authentically represent global financial markets, which we then analyze through complex simulations of trading behaviors. We hold a positive outlook on the potential of quantum optimization to elevate our simulations beyond what classical supercomputing can achieve, further enhancing our research capabilities. Recognizing the ever-changing nature of financial markets, we design AI algorithms that are capable of real-time adaptation and learning, enabling us to uncover intricate relationships between numerous financial assets, classes, and markets. The convergence of neuroscience-inspired models, quantum algorithms, and machine learning in systematic trading is still largely unexplored, presenting an exciting frontier for future research and innovation. By challenging the limits of existing methodologies, we aspire to transform the formulation and execution of trading strategies in this dynamic environment, paving the way for unprecedented advancements in the field. As we continue to explore these avenues, we remain committed to advancing the intersection of technology and finance.

What is Microsoft Cognitive Toolkit?

The Microsoft Cognitive Toolkit (CNTK) is an open-source framework that facilitates high-performance distributed deep learning applications. It models neural networks using a series of computational operations structured in a directed graph format. Developers can easily implement and combine numerous well-known model architectures such as feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). By employing stochastic gradient descent (SGD) and error backpropagation learning, CNTK supports automatic differentiation and allows for parallel processing across multiple GPUs and server environments. The toolkit can function as a library within Python, C#, or C++ applications, or it can be used as a standalone machine-learning tool that utilizes its own model description language, BrainScript. Furthermore, CNTK's model evaluation features can be accessed from Java applications, enhancing its versatility. It is compatible with 64-bit Linux and 64-bit Windows operating systems. Users have the flexibility to either download pre-compiled binary packages or build the toolkit from the source code available on GitHub, depending on their preferences and technical expertise. This broad compatibility and adaptability make CNTK an invaluable resource for developers aiming to implement deep learning in their projects, ensuring that they can tailor their tools to meet specific needs effectively.

Media

Media

Integrations Supported

Integrations Supported

AI Skills Navigator
Alteryx
AssurX
AuraQuantic
Azure Data Science Virtual Machines
Azure Database for MariaDB
Microsoft Dynamics 365 Finance
Microsoft Dynamics Supply Chain Management
Microsoft Power Platform

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Neuri

Date Founded

2018

Company Location

Singapore

Company Website

www.neuri.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

docs.microsoft.com/en-us/cognitive-toolkit/

Categories and Features

Deep Learning

Not specified

Finance

Not specified

Neural Network

Not specified

Quantum Computing

Not specified

Categories and Features

Deep Learning

Convolutional Neural Networks

Neural Network

Not specified

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