GitHub / PramodRawat157 / Data-Analysis-with-Python---IBM-Data-Science
To import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. I will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them.
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PURL: pkg:github/PramodRawat157/Data-Analysis-with-Python---IBM-Data-Science
Stars: 0
Forks: 1
Open issues: 1
License: gpl-3.0
Language: Jupyter Notebook
Size: 9.02 MB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: almost 2 years ago
Pushed at: over 2 years ago
Last synced at: almost 2 years ago
Commit Stats
Commits: 20
Authors: 1
Mean commits per author: 20.0
Development Distribution Score: 0.0
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/PramodRawat157/Data-Analysis-with-Python---IBM-Data-Science
Topics: dataanalysis, dataviz, datawrangling, googlecolab, hypothesis-tests, jupyter-notebook, linear-regression, matplotlib-pyplot, modeldevelopment, modelevaluation, numpy-arrays, pandas-dataframe, python3, refinement, scikitlearn-machine-learning, scipy, seaborn-plots, stastistical-sampling