**Object-Oriented Programming** is a methodology or paradigm to design a program using classes and objects. Basically it is used to bridge the gap between the real world entity and our code.

**Advantages of OOPS**

- OOP is faster and easier to execute
- OOP provides a clear structure for the programs
- OOP…

K-nearest neighbors (KNN) algorithm is a type of supervised ML algorithm which can be used for both classification as well as regression predictive problems. However, it is mainly used for classification predictive problems in industry. The following two properties would define KNN well −

**Lazy learning algorithm**− KNN is…

Linear regression is one of the very basic forms of machine learning where we train a model to predict the behaviour of your data based on some variables. …

Machine Learning uses statistics, probability, algorithms to learn from data and provide insights which can be used to build smart applications.

Probability and statistics are related areas of mathematics which concern themselves with analyzing the relative frequency of events.

**Probability** is given by the number of ways the particular event…

Linear algebra is a branch of mathematics that is widely used throughout science and engineering. Yet because linear algebra is a form of continuous rather than discrete mathematics, many computer scientists have little experience with it.

A good understanding of linear algebra is essential for understanding and working with many…

Aspiring Machine Learning Engineers often tend to ask “*What is the use of Mathematics for Machine Learning when we have computers to do it all?*”. Well, that is true. Our computers have become capable enough to do the math in split seconds where we would take minutes or hours to…

OpenCV is one of the most popular computer vision libraries. If you want to start your journey in the field of computer vision, then a thorough understanding of the concepts of OpenCV is of paramount importance. …

*Is the practice of visualizing data in graphs, icons, presentations and more. It is most commonly used to translate complex data into digestible insights for a non-technical audience.*

Matplotlib is one of the most powerful tools for data visualization in Python. It** **tries to make easy things easy and hard…

Pandas is a catch-all Python library; a resource for doing data analysis and manipulation; any kind of data processing, analyzing, filtering, and aggregating. Pandas can be used for just about any process where you’re trying to gain insight from data using code.

**When might Pandas be used in the workplace?**

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NumPy is the fundamental package for scientific computing with Python and it is the library Pandas, Matplotlib and Scikit-learn builds on top off. You might think “what’s the point of using NumPy when I could be using these libraries?” …