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data science

What is Machine Learning?

Answering the question of what is “machine learning” has been a puzzle to many, especially to those who are new in this field. Perhaps let us start by going through some examples of the machine learning examples that you might have come across having no idea they are driven by machine learning. virtual personal assistants

machine learning

How supervised Machine Learning works.

A model is prepared through a training process in which it is required to make predictions and it is corrected when those predictions are wrong. Input data is called training data and has a known label or result such as spam/not-spam or a stock price at a time. The training process continues until the model

machine learning

Demystifying Machine Learning Algorithms by Learning Style-Series1-Introduction.

Machine learning algorithms learn from the provided data and get trained to make “informed decisions”. An example is after training on a set of experimental weather data, a machine learning model can make an informed decision like, the weather is going to rain tomorrow or not. So as explained above, machine learning algorithms has to

machine learning

Getting Started with Machine Learning using Python-Data Preprocessing.

Step 1: Importing the required libraries. These two are essential libraries which we will import every time. Numpy is a library that contains Mathematical functions. Pandas is the library used to import and manage the data sets. Step 2: Importing the Data set Data sets are generally available in CSV format. A CSV file stores

machine learning

R vs Python for Machine Learning

Python and R are the two most commonly used languages in data science. Today, most of the novices get confused, whether they should use R or Python to kick-start their careers in the field of data science. I am gonna tell you the long and the short of both of these topics. Introduction R is

machine learning

The Reign of Machine Learning.

As technological advances continue to rise globally, smart production systems require innovative solutions to increase the sustainability of businesses while reducing costs. This means that businesses have to embrace emerging technologies ranging from IoT, Artificial intelligence, 5G, robotics, biometrics, 3D printing, and many more. AI-driven technologies such as cloud computing, big data, cognitive analysis, machine