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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

JULY 25, 2023

These models may include regression, classification, clustering, and more. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc. ETL Tools: Apache NiFi, Talend, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Best Resources for Kids to learn Data Science with Python

Pickl AI

MAY 31, 2023

After that, move towards unsupervised learning methods like clustering and dimensionality reduction. Accordingly, you need to make sense of the data that you derive from the various sources for which knowledge in probability, hypothesis testing, regression analysis is important.

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Introduction to R Programming For Data Science

Pickl AI

JULY 10, 2023

Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. It provides functions for descriptive statistics, hypothesis testing, regression analysis, time series analysis, survival analysis, and more. How is R Used in Data Science?

Data Science

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Best Resources for Kids to learn Data Science with Python

Introduction to R Programming For Data Science

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