# ML-Machine-Learning
| GitHub Repo |🍭 [ML](https://github.com/akashdip2001/ML-Machine-Learning) 🍭|🐥 [Pandas](https://github.com/akashdip2001/ML-Machine-Learning/tree/main/pandas) 🐥|❌ [numPy](https://github.com/akashdip2001/ML-Machine-Learning/tree/main/numPy) ❌| |-------------------- |-------------------- |-------------------- |-------------------- | | WebSite => |🍭 [ML](https://akashdip2001.github.io/ML-Machine-Learning/) 🍭|🐥 [Pandas](https://akashdip2001.github.io/ML-Machine-Learning/pandas.html) 🐥|❌ [numPy](https://akashdip2001.github.io/ML-Machine-Learning/numPy.html) ❌| |-------------------- |-------------------- |-------------------- |-------------------- | --- ![ml](https://github.com/akashdip2001/ML-Machine-Learning/raw/main/ML/img/ml_roadmap01.jpg) ![ml](https://github.com/akashdip2001/ML-Machine-Learning/raw/main/ML/img/ml_roadmap02.jpg) # Jupyter Notebook // JupyterLab // .ipynb ### Command Mode Shortcuts (press Esc to activate) - **A**: Insert cell above - **B**: Insert cell below - **D, D** (press D twice): Delete selected cell - **Y**: Change cell to code mode - **M**: Change cell to markdown mode - **Shift + Arrow**: Select multiple cells - **Shift + M**: Merge selected cells - **Ctrl + Enter**: Run selected cell - **Shift + Enter**: Run cell and select below - **Alt + Enter**: Run cell and insert new cell below ### Edit Mode Shortcuts (press Enter to activate) - **Ctrl + /**: Comment/uncomment selected lines - **Tab**: Code completion or indent - **Shift + Tab**: Tooltip (for function arguments) - **Ctrl + Shift + -**: Split cell at cursor - **Ctrl + Shift + P**: Command palette (access to all commands) ### Navigation Shortcuts (in both modes) - **Up Arrow / Down Arrow**: Move up/down one cell - **Ctrl + Home**: Go to first cell - **Ctrl + End**: Go to last cell - **Ctrl + G**: Go to specific cell by number - **Shift + L**: Toggle line numbers ### Other Useful Shortcuts - **Esc + F**: Find and replace - **Esc + O**: Toggle cell output - **Esc + H**: Show keyboard shortcuts help dialog - **Esc + I, I**: Interrupt kernel - **Esc + 0, 0**: Restart kernel - **Ctrl + Shift + Enter**:Run All Cells --- # [Pandas](https://github.com/akashdip2001/ML-Machine-Learning/tree/main/pandas) ### Downlod [Pythin](https://www.python.org/downloads/_) Run Command Prompt as Administrator: - Right-click on the Command Prompt icon in the Start menu. - Select "Run as administrator". - Confirm the User Account Control prompt if prompted. ```python !pip install pandas !pip install jupyter # If you want to install matplotlib as well, uncomment the line below # !pip install matplotlib !jupyter notebook --version ``` ``` jupyter notebook ``` ![Screenshot (38)](https://github.com/akashdip2001/ML-Machine-Learning/assets/81384987/bd3b3e3a-5d70-41a2-b412-14f1f109fc8e) ![Screenshot (39)](https://github.com/akashdip2001/ML-Machine-Learning/assets/81384987/d1b0208d-eca9-42d1-a800-8ca1cda97eb4) ```python import numpy as np import matplotlib.pyplot as plt # Data for plotting t = np.arange(0.0, 2.0, 0.01) s = 1 + np.sin(2 * np.pi * t) fig, ax = plt.subplots() ax.plot(t, s) ax.set(xlabel='time (s)', ylabel='voltage (mV)', title='About as simple as it gets, folks') ax.grid() plt.show() ``` ![png](https://github.com/akashdip2001/ML-Machine-Learning/raw/main/pandas/output_0_0.png) | more about [pamdas](https://github.com/akashdip2001/ML-Machine-Learning/tree/main/pandas) | |--- # [numPy](https://github.com/akashdip2001/ML-Machine-Learning/tree/main/numPy) #### [documentation](https://numpy.org/doc/stable/reference/) ```python pip install numpy python.exe -m pip install --upgrade pip pip install jupyter ``` | python 10h => |🍭 [SourceCode](https://github.com/akashdip2001/Python-Course-10h) 🍭|🐥 [Notes 10h]() 🐥|❌ [complete Notes](https://www.codewithharry.com/notes/) ❌| |-------------------- |-------------------- |-------------------- |-------------------- | ```html 7296 body { zoom: 100%; /* Default zoom level */ } 7522