This repository is structured to help you navigate and utilize the notes effectively. Below is the recommended structure:
Akash_AI_ML_Notes/
├── 1_SQL/ # Learn about basic SQL Queries
├── 2_DATA SCIENCE LIBRARIES # Learn about the libraries required for Data Science
├── 3_Maths_for_DS_AIML # Learn about basic Maths and statistics for DS and AIML
├── 4_Machine Learning(ML) # Learn about ML algorithsm & training ML models
└── README.md # Project overview and instructions
The uv
package manager is a Python ecosystem tool similar to npm
in the JavaScript ecosystem. It allows you to manage dependencies, scripts, and configurations for your projects efficiently. If you're familiar with npm
, you'll find uv
intuitive and powerful for managing AI/ML or Python based projects.
Steps to setup your system environment to use these notes optimally:
-
Install Python from the official docs: Docs
-
Install uv using pip:
pip install uv # For windows pip3 install uv # For Mac/Linux
-
Install the requirements using uv from the requirements.txt:
uv add -r requirements.txt # Or let uv install from the pyproject.toml uv pip install .
-
If you need to add any dependency for your learning locally on your system, use these commands:
uv add <pkg_name> # Install package using uv uv pip freeze > requirements.txt # Freeze your dependencies to used on any system
-
In VS code in .ipynb files we need to select the kernel from the
.venv
-
If you want to use jupyter notebooks in your browser view not in vs code, use these commands in the
root directory
of this project:.\.venv\Scripts\Activate.ps1 # For Windows source .venv/bin/activate # For Unix based OS (Mac/Linux):
-
These will activate the virtual environment for you and we can use
jupyter notebook
orjupyter lab
to work in the default browser view