Project Development: Machine Learning, Data Analytics, and Data Science

Hypothesis-based versus data-driven analysis

“Only those data analysts who are given time to explore and analyze data thoughtfully and thoroughly are consistently successful.”

Data Identification and Prioritization

Use Augmented data besides Data Pipeline

Analytics Sandbox

Characterizing the Data—Exploring a Single Variable

Data: Descriptive analysis options

Find: Distribution of quantitative variables

Reference: [1]. Gregory S. Nelson. The Analytics Lifecycle Toolkit: A Practical Guide for an Effective  Analytics Capability,  John Wiley & Sons © 2018

Data Analytics, Machine Learning

Data Analytics, Machine Learning, Data Science