Hi there,
This is the first article in which we are going to cover all the statistics and probability theory we need to learn data science. In this series of articles we are going to start from here and gradually move into data analysis using statistics we learn. Then we will build, use machine learning algorithms to solve real-world data science problems. Of course, if you want to get started with data science, knowing programming is a necessity. So I welcome you to check out my python tutorials series as well.

From my previous article where we talked about introduction to data science, we know that Data science is the field of study that uses mathematics, programming, and domain knowledge to extract meaningful insights from data. Data scientists would apply machine learning algorithms to data such as numbers, texts, images videos, and more to produce artificial systems that perform tasks that require human intelligence. Using these systems we extract insights that can be used in our business to grow.
So we know that mathematics and statistics are essential for learning data science. Mathematics and statistics are the backbone of every machine learning algorithm we will be using in the data science field. So having good knowledge of maths and statistics will help you to understand data as well as apply algorithms to them. …


Hi there,
In this article let’s talk about data types and variables in python.

So this would be the second article about python for data science. In the first article, we saw how to write your first program. You can see that article from this link.

Okay before we talk about variables and data types let’s focus on one unique thing about the python language.

Indentation

In the python language, when we write codes we have to be careful about Indentations. What that means is spaces at the beginning of a code line.
If you are done writing one statement in python you must begin in a new line writing your next statement. …


Python is a high-level, interpreted, interactive, and object-oriented scripting language.

Okay, that’s a lot of information right there. Let’s breaks those down.

  1. Python is a high-level language- Python easier to read, write, and maintain. To run the program that’s written in a high-level language, we have to translate that code into machine language by a compiler or an interpreter (Interpreter explained in the next point).
  2. Python is Interpreted − Python is processed at runtime by the interpreter. We do not need to compile our program before executing it. After we compiled we will have a working program to run. But in interpreted languages, we will only know if it’s working or not when we are running the program. …

What is Data Science?

Data science is the field of study that uses mathematics, programming, and domain knowledge to extract meaningful insights from data. Data scientists would apply machine learning algorithms to data such as numbers, texts, images, videos, and more to produce artificial systems that perform tasks that require human intelligence. Using these systems, we extract insights from the data and use them to make better decisions in various situations.

data science, introduction to data science
data science, introduction to data science

We live in a world that is full of data. From traffic cameras to big corporations produces tons of data every day every minute. …

About

Rashal Ismath

Software Developer || Data Science enthusiast aboutismath.herokuapp.com/

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