Data Science

-
Several days ago, I've shared a link as a post in my LinkedIn profile, which gives a better introduction about Data Science.

Here, again I would like to share the same link, so that it may helpful to many.....

Please follow the link...

https://www.edureka.co/blog/what-is-data-science/

Comments

Post a Comment

Popular posts from this blog

Structural Equation Modelling - A basic introduction.

-
Structural Equation Modelling - A basic introduction. Hi Folks, before I begin, I would like to give a overview about the content in this post. This article gives a theoretical overview about the Structural Equation Modelling. This article is targeted and primarily helpful for beginners. The main reason why I have been intended to write this article is to provide an easy understanding about the concept of SEM in a layman language. I humbly admit that, I'm not going to deal with the entire concepts, principles and explanations related to SEM. However, I hope that this article at least provides you a better idea of the rudiments lying under the hood of SEM. Let me give a quick introduction about myself(Sorry for the interruption). I'm a Software Engineer (Business Intelligence & Analytics). A person with ardent interest and curiosity in dealing with data. Data Science and Machine Learning enthusiast. Data Science and Machine Learning blogger. An R & Python(jus...
Read more

An Introduction to Factor Analysis

-
An Introduction to Factor Analysis Hi Guys, in this article I will be giving a theoretical overview about Factor Analysis. This article could also be considered as a continuation of my previous article on Structural Equation Modelling . Since a prior knowledge on Factor analysis is very important to have a better understanding of SEM, I would like to give separate and dedicated article related to Factor Analysis and Path Analysis. This article will cover the Factor Analysis and soon there will be a separate one for Path Analysis too. Lets get started, What exactly a Factor Analysis is? The theory behind the factor analysis is that, the information gained about the inter-dependencies between observed variables can be used later to reduce the set of variables in a dataset. In general, it can be considered as a Data reduction or Dimensionality reduction technique. It's objective is to find out the latent factors that create a commonality among the set of variables. The...
Read more

Machine Learning - a basic introduction with step by step implementation

-
Machine Learning - a basic introduction with step by step implementation Hi Guys, in this article, the rudiments in understanding the Machine Learning and the steps to implement it, has been discussed. I hope this would give you a better understanding of Machine Learning concepts. Let's get started, and begin with the very basic question, What is Machine Learning? Machine Learning(ML) is a sub-field of Computer Science and AI, and contributes to building systems that can learn from data without explicit programming. It has a strong predictive power, as the machine is fit and trained to find patterns in the data. Machine learning is a concept of teaching the machine with the huge volume of dataset and verify the accuracy with the new dataset. In Machine Learning, data is gathered to train a machine learning model, so it can understand patterns within the data. Once the model has been trained, it can be used it to predict the results of out-of-sample data, or d...
Read more