Machine Learning Services

K Nearest Neighbor (KNN) algorithm is one the simplest machine learning algorithms that depend on a supervised learning mechanism. It takes into consideration similarities between the newer data and available data, categorizing the similar ones.

Supervised machine learning algorithms depend upon labelled datasets whereas unsupervised machine learning algorithms depend upon unlabelled datasets. In supervised learning, input data is offered to the data model with the output whereas in unsupervised learning, only input data is offered to the model.

Precision accuracy in machine learning is the fraction of relevant instances among the retrieved ones, while information retrieval and classification are on in pattern recognition. Recall is the fraction of relevant instances that were obtained.

A machine learning classifier is an algorithm that on an automatic basis, categorizes data into many sets of classes. It leverages some data to understand the relationship between the input variables to the class.

Adaptive machine learning is a type of machine learning in which dynamic inputs are utilized after an initial static model has been assumed. It needs effective reinforcement learning, online learning, and adaptive learning from a sample size.

A decision tree algorithm is a type of supervised machine learning wherein the data is split based on a certain parameter, on a continuous basis. It consists of two basic parameters – decision nodes and leaves.

As such, there are many languages suited for machine learning, but the most popular ones are Python, C++, Java, R, JavaScript, LISP.