https://github.com/rifat392000/statisticsfordatascience

https://github.com/rifat392000/statisticsfordatascience

calculas data-science data-science-projects decission-tree linear-algebra logistic-regression machine-learning-algorithms matplotlib numpy-arrays pandas-dataframe probability python python-3 python-libary random-forest seaborn statistics svm visualization

Last synced: 5 days ago
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• Host: GitHub
• URL: https://github.com/rifat392000/statisticsfordatascience
• Owner: Rifat392000
• License: mit
• Created: 2023-10-08T13:11:11.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-17T09:35:42.000Z (about 1 year ago)
• Last Synced: 2024-11-16T13:08:33.067Z (2 months ago)
• Topics: calculas, data-science, data-science-projects, decission-tree, linear-algebra, logistic-regression, machine-learning-algorithms, matplotlib, numpy-arrays, pandas-dataframe, probability, python, python-3, python-libary, random-forest, seaborn, statistics, svm, visualization
• Language: Jupyter Notebook
• Homepage:
• Size: 1.18 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# Statistics for Data Science

The objective of the course is to introduce the statistical methods, techniques and tools that are essential for Data science domain. The course focuses on examining descriptive and inferential statistics and analyzing The output of these methods. The course also emphasizes techniques for result estimation and anomaly detection. Statistical machine learning methods that "learn" from data will be also introduced.