5 Difference between Data Science and Machine Learning

Data Science

Key Components: Data collection, data cleaning, data analysis, data visualization

Goal: To solve complex problems, make data-driven decisions, and generate actionable insights

Machine Learning

Key Components: Supervised learning, unsupervised learning, reinforcement learning, and deep learning

Goal: To develop predictive models and algorithms

Purpose and Scope of Data Science

Data Science is about understanding and extracting meaningful insights from data to support decision-making

Scope: Broad and encompasses data preprocessing, analysis, visualization

Purpose and Scope of Machine Learning

Machine Learning focuses on developing algorithms and models to make predictions

Scope: Narrower than Data Science, primarily centered around algorithm development

Collaboration

Data Scientists often work closely with Machine Learning Engineers to deploy models in real-world applications

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