## Natural Language Processing Text Vectorization Approaches

Introduction It always needs to transform natural language either text or audio into numerical form for Natural Language Processing to work. Text vectorization approaches are very best choices for traditional machine learning algorithms. They can support converting text to numeric feature vectors. For this purpose, some techniques namely Bag of Words and td-idf vectorization are […]

## Important Clustering Algorithms in Machine Learning

Introduction Clustering is a Machine Learning method. It implicates the grouping of data points. It is an unsupervised machine learning task. In which, we draw references from datasets consisting of input data without labelled responses. With a clustering algorithm, we give the algorithm a lot of input data with no labels and let it find […]

## What Are Probabilistic Models in Machine Learning?

Introduction Probabilistic Models in Machine Learning is the use of the codes of statistics to data examination. It was one of the initial methods of machine learning. It’s quite extensively used to this day. Individual of the best-known algorithms in this group is the Naive Bayes algorithm. Probabilistic modelling delivers a framework for accepting what […]

## Linear Regression for Machine Learning

Introduction Linear regression is a linear methodology for modeling the relationship between a scalar response and one or more explanatory variables in statistics. The situation of one explanatory variable is called simple linear regression and for more than one, the process is called multiple linear regressions. Description The connections are modeled using linear predictor functions […]

## Dimensionality Reduction in Machine Learning

Introduction Dimensionality Reduction in machine learning is the conversion of data from a high-dimensional space into a low-dimensional space. This is so that the low-dimensional representation recalls certain expressive properties of the original data that is preferably close to its basic dimension. At work in high-dimensional spaces may be unwanted for many reasons for example; […]

## Learning for Structured Prediction

Introduction Structured prediction is the main term for supervised machine learning techniques. Those techniques are involved predicting structured objects, instead of scalar discrete or real values. Structured prediction models are normally trained by means of observed data. In which the true value is used to regulate model parameters similar to usually used supervised learning techniques. […]

## Einstein’s Special Theory Of Relativity

Einstein Special Theory Of Relativity Introduction Einstein’s theory of special relativity explains how time, space & light are inter-connected ~ as objects travel near the speed of light. The equation E = mc2 means energy equals mass times the speed of light squared. It shows that energy (E) and mass (m) are inter-changeable ~ they […]

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