Flipboard

JUNE 12, 2025

When you understand distributions, you can spot data quality issues instantly. When you know hypothesis testing, you know whether your A/B test results actually mean something. Hypothesis testing gives you the framework to make valid and provable claims. Part 5: What Should Be Your Learning Strategy?

Data Science 151

Data Science Natural Language Processing Hypothesis Testing Machine Learning 151

Dataconomy

MAY 16, 2023

Data preprocessing and feature engineering: They are responsible for preparing and cleaning data, performing feature extraction and selection, and transforming data into a format suitable for model training and evaluation. They use data visualization techniques to effectively communicate patterns and insights.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

MAY 30, 2024

Overview of Typical Tasks and Responsibilities in Data Science As a Data Scientist, your daily tasks and responsibilities will encompass many activities. You will collect and clean data from multiple sources, ensuring it is suitable for analysis. Data Cleaning Data cleaning is crucial for data integrity.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52