New Machine Learning Algorithms in 2021

Machine Learning is becoming the future of mankind. Machine Learning algorithms are changing the definition of manual tasks, allowing computers to perform menial jobs such as responding to emails, right down to performing exhaustive and difficult surgeries, and much more.

Machine Learning algorithms help computers to perform the assigned tasks in the most precise, and fastest way possible, along with the ability to learn, grasp and adapt accordingly. These algorithms not only make the computers intelligent and smart but also adaptive, so they can perform their tasks even if there are changes in the data, responses, etc. Machine Learning and its applications are picking up rapid pace as the possibilities are endless and the benefit that it brings to a plethora of industries is astounding and unbelievable.

The commandments of tomorrow

Let us look at the new Machine Learning Algorithms in 2021, that are gearing up to hit the markets and revolutionize the way we work, function, and perceive the world.

Linear Regression

Imagine arranging identical wooden boxes in the increasing order of their weight, but the catch is you cannot weigh each box. This is where liner regression comes in, mapping the height, width, etc. (visual analysis), and arranging the data accordingly with the help of parameters. This is done by establishing a relationship between the independent and dependent variables, and fitting them into a line (Y=a*X+b).

Decision Tree

This is one of the most popular machine learning algorithms, which is a supervised learning algorithm, built to classify problems. It works for categorical as well as continuous dependent variables. This algorithm involves dividing the population into two homogenous sets based on the most significant independent variables or characteristics.

SVM Algorithm

This is a classification algorithm where one can plot raw data points in an n-dimension space. You can select the value of n depending upon the number of features one has of a particular point/data, making it extremely easy to classify and study the data. Further, classifiers can be used to split and present the data on a graph, making it easier to present and map the information in a precise and accurate way.

KNN Algorithm

This algorithm can solve classification as well as regression problems, but the former being widely used in the Data Science industry to solve problems. It stores all available cases and classifies new cases by the majority of its k-neighbor. To simply understand, if you wish to know more about a person, you talk to his acquaintances, friends, neighbors, family, etc.

Dimensionality Reduction Algorithms

Today’s world is generating insane amounts of data each day by different organizations both private and public. Data scientists know the importance of this data, but it is a tedious task to identify patterns, trends, etc. Dimensionality reduction algorithms like Missing Value Ratio, Decision Tree, Factor Analysis, and Random Forest can help them find those hidden patterns, trends, and much more.

Random Forest Algorithm

The name comes from the Decision Tree algorithm as it is a collection of decision trees. Each tree is classified, and votes, which helps classify new data into its rightful place. The forest chooses the class of the new data concerning the maximum common features it shares with the existing decision trees, making classification precise and easy.

De-Coding the Future!

These Machine Learning Algorithms are bringing a dynamic change in the working and functioning of enterprises, in turn leading to more advanced and productive products and services for the customers. Since new machine learning algorithms and their applications are being developed and discovered, it becomes an exciting wait to see whether it unfolds tremendously or goes down as the biggest hype of the century! These algorithms are just the beginning of a new world, where tech is much more than just a gadget or some tool to help us, but a means to achieve something that we could not earlier due to fewer resources and technology – The Future!

“Computers are able to see, hear and learn.  Welcome to the future.”

Dave Waters

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