Dataconomy

MAY 16, 2023

Mathematical and statistical knowledge: A solid foundation in mathematical concepts, linear algebra, calculus, and statistics is necessary to understand the underlying principles of machine learning algorithms. They use data visualization techniques to effectively communicate patterns and insights.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

MAY 29, 2024

Skills in data manipulation and cleaning are necessary to prepare data for analysis. Data Scientists frequently use tools like pandas in Python and dplyr in R to transform and clean data sets, ensuring accuracy in subsequent analyses. Data Visualisation Visualisation of data is a critical skill.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

The following figure represents the life cycle of data science. It starts with gathering the business requirements and relevant data. Once the data is acquired, it is maintained by performing data cleaning, data warehousing, data staging, and data architecture. What is deep learning?

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Analysis: This step involves applying statistical and Machine Learning techniques to analyse the cleaned data and uncover patterns, trends, and relationships.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52