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Anomaly Detection of Time Series Data Using Machine Learning & Deep Learning

Time Series is defined as a set of observations taken at a particular period of time. For example, having a set of login details at regular interval of time of each user can be categorized as a time series. On the other hand, when the data is collected at once or irregularly, it is not taken as a time series data.

Overview of Artificial Neural Networks and its Applications

The term ‘Neural’ is derived from the human (animal) nervous system’s basic functional unit ‘neuron’ or nerve cells which are present in the brain and other parts of the human(animal) body. Dendrite - It receives signals from other neurons.

Log Analytics With Deep Learning And Machine Learning

Deep Learning is a type of Neural Network Algorithm that takes metadata as an input and process the data through a number of layers of a non-linear transformation of the input data to compute the output. This algorithm has a unique feature i.e. automatic feature extraction.

Understanding Log Analytics, Log Mining & Anomaly Detection

With technologies such as Machine Learning and Deep Neural Networks (DNN). These technologies employ next generation server infrastructure that spans immense Windows and Linux cluster environments.

Build, Deploy, Manage & Secure Continuous Delivery Pipeline & Analytics Stack.

NexaStack - DevOps & Serverless Computing Platform

Elixir Data - Modern Data Integration Platform

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