Log Analytics With Deep Learning And Machine Learning

Machine Learning

Machine Learning is a set of the technique used for the processing of large data by developing algorithms and set of rules to deliver the required results to the user. It is the technique used for developing automated machines on the basis of execution of algorithms and set of defined rules.

In Machine Learning data is fed and set of rules are executed by the algorithm. Therefore, techniques of Machine Learning can be categorized as instructions that are executed and learned automatically to produce optimum results.

It is performed without any human interference. It automatically turns the data into patterns and goes deep inside the system for the detection of production problem automatically.

Deep 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 the non-linear transformation of the input data to compute the output.

This algorithm has a unique feature i.e. automatic feature extraction. This means that this algorithm automatically grasps the relevant features required for the solution of the problem.

This reduces the burden on the programmer to select the features explicitly. This can be used to solve supervised, unsupervised or semi-supervised type of problems.

In Deep Learning Neural Network, each hidden layer is responsible for training the unique set of features based on the output of the previous layer. As the number of hidden layers increases, the complexity and abstraction of data also increase.

It forms a hierarchy from low-level features to high-level features. With this, it becomes possible that Deep Learning Algorithm can be used to solve higher complex problems consisting of a large number of non-linear transformational layers.

Difference Between Neural Network and Deep Learning Neural Network

Neural Network is a network that can use any network such as feedforward or recurrent network having 1 or 2 hidden layers. But, when the number of hidden layers increases i.e. more than 2 than that is known as Deep Learning Neural Network.

Neural Network is less complex and requires more information about features for performing feature selection and feature engineering method. On the other hand, Deep Learning Neural Network does not require any information about features rather they perform optimum model tuning and model selection on their own.

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