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Channel 9 was a Microsoft website for hosting videos and podcasts that Microsoft employees create. [ 1 ] Launched in 2004 when Microsoft's corporate reputation was at a low, [ 2 ] Channel 9 was the company's first blog .
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning ...
Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery in databases).
Microsoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington. [2] Founded in 1975, the company became highly influential in the rise of personal computers through software like Windows, and the company has since expanded to Internet services, cloud computing, video gaming and other fields.
Deep Learning Studio is a software tool that aims to simplify the creation of deep learning models used in artificial intelligence. [1] It is compatible with a number of open-source programming frameworks popularly used in artificial neural networks , including MXNet and Google's TensorFlow .
scikit-learn, an open source machine learning library for Python; Orange, a free data mining software suite, module Orange.ensemble; Weka is a machine learning set of tools that offers variate implementations of boosting algorithms like AdaBoost and LogitBoost
This image represents an example of overfitting in machine learning. The red dots represent training set data. The green line represents the true functional relationship, while the blue line shows the learned function, which has been overfitted to the training set data. In machine learning problems, a major problem that arises is that of ...
Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...