KDnuggets

SEPTEMBER 13, 2023

As you progress in your data science journey, here are the elementary statistics you should know.

Python 94

Python Data Science Data 94

Knowledge Hut

DECEMBER 29, 2023

Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization. However, transitioning to Data Science or beginning a career in data science fields as a novice is not simple.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

MAY 2, 2024

Machine learning is a field that encompasses probability, statistics, computer science and algorithms that are used to create intelligent applications. Automation and machine learning have changed our lives. But how can you, as a beginner, learn about the latest technologies and the various diverse fields that contribute to it?

Machine Learning 98

Machine Learning Algorithm Datasets Deep Learning 98

ProjectPro

MARCH 7, 2016

Big Data is in the middle of its journey, offering various life-changing career opportunities. If your career goals are headed towards Big Data, then 2016 is the best time to hone your skills in the direction, by obtaining one or more of the big data certifications. Table of Contents Why you should take a big data certification?

Big Data 40

Big Data Certification Hadoop Big Data Skills 40

Knowledge Hut

MAY 1, 2024

With that being said, let’s jump into the details about the types of big data and the role of statistics in data science. How the basics of statistics will serve as a foundation to manipulate data in data science The basics of statistics include terminologies and methods of applying statistics in data science.

Data Science 52

Data Science Datasets Algorithm Machine Learning 52

Knowledge Hut

FEBRUARY 7, 2023

Statistics is a well-known field primarily concerned with data collecting, data organization, data analysis, data interpretation, and data visualization. In the past, statisticians, economists, and business leaders used statistics to calculate and portray relevant information in their respective fields. Why Python for Statistics?

Data Science 52

Data Science Python Datasets Data 52