Installed Key Python Libraries for Machine Learning
Pandas
pip install pandas
Successfully installed pandas, numpy, python-dateutil, pytz, tzdata, and six.
Use: Essential for data manipulation and analysis through DataFrames and Series.
Scikit-learn
pip install scikit-learn
Installed scikit-learn, joblib, scipy, and threadpoolctl.
Use: A powerful library for machine learning, including classification, regression, and clustering.
Matplotlib
pip install matplotlib
Installed matplotlib along with dependencies: cycler, kiwisolver, pyparsing, fonttools, pillow, and more.
Use: Widely used for creating static, animated, and interactive visualizations in Python.
ALGORITHM
IRIS DATASET
OUTPUT
DENSITY_PLOTS
HISTOGRAMS
git checkout -b feature-24MCR075
Purpose: Creates a new branch named feature-24MCR075 and immediately switches to it.
Use case: Ideal when starting work on a new feature, bug fix, or task. Keeps changes isolated from the main branch.
git branch
Purpose: Lists all the branches in the current repository.
Use case: Helps verify which branches exist and highlights the currently checked-out branch with an asterisk (*).
git status
Purpose: Shows the current status of the working directory and staging area.
Use case: Lets you see which files are modified, staged, untracked, or ready to commit.
git add .
Purpose: Adds all modified and new files in the current directory (and subdirectories) to the staging area.
Use case: Prepares all changes to be included in the next commit.
git push origin feature-24MCR075
Purpose: Pushes the feature-24MCR075 branch and its commits to the remote repository (origin).
Use case: Shares your branch with others or uploads it to platforms like GitHub/GitLab for collaboration or pull requests.
