Introduction To The Life Cycle Of Data Science

The Data Science Lifecycle is focused on the application of machine learning and various analytical methods to extract insights from data to achieve a company goal. The complete procedure includes several activities, such as data cleansing, preparation, modelling, and model evaluation. It is a time-consuming process that could take months to complete

The lifecycle of the data science process:

Business Understanding

The overall cycle revolves around the company's objectives. Considering that the study's ultimate...

Should You Learn Linux in 2022 If You Want To Work In Data Science?

Introduction

One of the most distinctive and hard aspects of Data Science is a wide skill set frequently necessitated. While a conventional scientist might need to read scientific papers or research data with some basic statistical and hypothetical testing, Data Scientists perform the same with the addition of some advanced statistical and hypothetical testing.

Machine-learning
Programming
Business administration
Pipeline and API building

These are, in my opinion, important figures to consider while considering...

The Future Of Data Analysis Depends On Data Preparation
Overview:
With the rise in the amount of data, data analysis has become so vital for companies. The goal is to provide companies with solutions that allow them to get the most out of their data on a consistent basis. Data benefits the company in a number of ways, including supporting fact-based decision-making and expanding the range of data-focused products. Many trends are fast gaining traction in the data analytics business.
In this article,...

4 Best Data Science Projects In Healthcare That Will Get You Hired


Are you looking for data science projects in the healthcare industry as part of your career? No worries. In this post, you'll learn about a few healthcare projects that will help you land a job in a data science career.
Medical Imaging
Medical imaging is the most prominent use of data science in the healthcare sector. Imaging methods include X-rays, MRIs, and CT scans. However, it is challenging for doctors...

Can A Non-Programmer Succeed In A Data Science And Machine-Learning Career?

The demand for Machine Learning and Data Science has grown tremendously as a result of the constant creation of data. Due to this demand, many non-IT professionals have entered the field of Data Science. This blog is aimed at non-IT workers who want to pursue a career in Data Science, AI, and Machine Learning but have no prior expertise with programming languages and tools.

Data is essential for growing businesses, solving...

How Much Is Math Necessary to Become a Data Scientist?

Have you thought about pursuing a career in data science but been turned off by the maths requirements?
While data science is based on a foundation of mathematics, the quantity of mathematics required to become a professional data scientist may be less than you expect.

There are three major topics in the data science area:

Calculus, linear algebra, and statistics are the popular topics commonly used when searching for data science maths...