Jupyter Notebook

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Lecture 4:- Jupyter Notebook

Jupyter Notebook is an interactive computing environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It is widely used in data science, scientific research, and education due to its flexibility and ease of use. The name "Jupyter" is derived from the combination of three core programming languages it supports: Julia, Python, and R.

Key features of Jupyter Notebook include:

Notebook Interface: Jupyter Notebook provides a web-based interface where you can create, edit, and execute code cells, as well as add formatted text, images, and equations using Markdown.

Code Cells: In a Jupyter Notebook, code is written and executed in code cells. Each cell can contain code in the selected kernel language (Python by default), and you can run individual cells or the entire notebook.

Markdown Cells: Jupyter supports Markdown cells, allowing you to add formatted text, headings, lists, links, images, and mathematical equations using LaTeX syntax.

Interactive Output: Jupyter Notebook allows you to view interactive visualizations, plots, and graphical outputs directly within the notebook itself.

Kernel Support: Jupyter supports multiple programming languages through its kernel system. By default, it comes with a Python kernel, but you can install additional kernels for languages like R, Julia, and others.

Data Exploration and Analysis: Jupyter Notebook is commonly used for data exploration, analysis, and visualization tasks in data science projects. Its ability to mix code with explanatory text makes it an ideal tool for data analysis workflows.

Easy Sharing: Notebooks can be saved and shared in various formats, including HTML, PDF, or as interactive notebooks on platforms like JupyterHub or Jupyter Notebook Viewer.

To run Jupyter Notebook, follow these steps:

Launch Jupyter: Open a terminal (or command prompt) and type jupyter notebook. This will start the Jupyter Notebook server and open a web browser with the Jupyter interface.

Create a New Notebook: In the Jupyter interface, click on "New" and select "Python 3" (or any other installed kernel) to create a new notebook. This will open a new notebook with an empty code cell.

Execute Code: You can type code into the code cells and press Shift + Enter to execute the code. The output will appear below the cell.

Markdown Cells: To create text cells, select "Markdown" from the dropdown menu in the toolbar and add your Markdown content.

Saving and Exporting: To save your work, click on "File" and choose "Save and Checkpoint." You can also download the notebook in various formats from the "File" menu.

Shutdown Notebook: After you are done working, click "File" and choose "Close and Halt" to shut down the notebook. You can then close the browser window and stop the Jupyter Notebook server by pressing Ctrl + C in the terminal.

Jupyter Notebook is a powerful tool for data exploration, data analysis, and interactive coding. It has become an essential part of the data science workflow due to its versatility and interactivity.

1. Machine Learning Understanding

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