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Nilavya Das
Nilavya Das

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Unleashing the Power of Statistical Analysis in Machine Learning: Exploring Common Methods and Techniques

Hello readers today, I want to talk about the importance of statistical analysis in machine learning.

Statistical analysis involves

  • collecting
  • organizing,
  • summarizing,
  • interpreting data

to find patterns, trends, and relationships. This helps us better understand the data and make informed decisions based on evidence.

Statistical Techniques are utilized by machine learning to learn from data and provide predictions or recommendations, especially for challenging problems that traditional programming methods find difficult to handle.

Statistical analysis helps us prepare data for machine learning, select the right features, evaluate model performance, and interpret results. Machine learning helps us discover new insights from the data, test hypotheses, and make predictions.

There are some common statistical methods used in machine learning such as

  • descriptive statistics,
  • inferential statistics,
  • correlation,
  • regression,
  • classification,
  • clustering,
  • and dimensionality reduction.

I hope you have enjoyed reading the blog and grain some knowledge in it. Please leave a comment below if you have any questions or feedback. Thank you for your time and attention!

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