what is cntk fr?

Microsoft's Cognitive Toolkit, called CNTK, is an open-source deep learning toolkit. Deep learning is the branch of AI that uses neural networks, software loosely inspired by how brain cells connect, to learn patterns from data. CNTK gives engineers and researchers a way to design, train, and run those networks. The toolkit describes a neural network as a directed graph: a flowchart where input data flows through a series of mathematical steps and produces a result at the other end. Each node in the graph either holds input values, holds parameters that the network learns, or performs a matrix operation on whatever comes in. From this building block, CNTK lets people combine common model types, including feed-forward networks, convolutional networks often used for images, and recurrent networks including LSTMs often used for sequences such as text or audio. Training uses stochastic gradient descent, a standard method that nudges parameters in small steps to reduce mistakes, with automatic differentiation to compute those adjustments. It can spread the work across multiple GPUs and multiple servers in parallel. You would reach for CNTK if you were building a deep learning model and wanted a framework with parallel, distributed training. APIs are available in Python, C++, C#/.NET, and Java, and there is a backend for Keras. One important note from the project itself: the README states that the 2.7 release is the last main release of CNTK, that there are no plans for new feature development beyond it, and that the team recommends operationalizing models through ONNX and the ONNX Runtime instead. The full README is longer than what was provided.