Setting Up Your Environment
Install the libraries with pip or conda and confirm they import correctly.
Syntax
pip install numpy pandas scikit-learnBefore writing AI code you need the libraries installed. The two common package managers are pip and conda.
Installing with pip
pip install numpy pandas matplotlib scikit-learn seaborn jupyterCheck it worked
Import each library and print its version. If there are no errors, you are ready.
Using a virtual environment (venv or conda env) per project keeps versions from clashing.
Example
import numpy, pandas, sklearn, matplotlib
print('numpy', numpy.__version__)
print('pandas', pandas.__version__)
print('sklearn', sklearn.__version__)
# numpy 1.26.4
# pandas 2.2.2
# sklearn 1.5.0When to use it
- A developer creates an isolated conda environment for each ML project so different projects can pin different numpy and scikit-learn versions without conflict.
- A CI pipeline runs pip install -r requirements.txt before training to guarantee every team member and server uses the same library versions.
- A new team member follows the setup script to install the full AI stack and verify it with version prints before touching any code.
More examples
Install AI stack with pip
Creates a virtual environment, activates it, and installs the complete Python AI stack in one pip command.
python -m venv .venv
source .venv/bin/activate
pip install numpy pandas matplotlib scikit-learn seaborn jupyter torchVerify imports and versions
Imports each library and prints its version so you can confirm the environment is set up correctly before starting a project.
import numpy as np
import pandas as pd
import sklearn
import matplotlib
import seaborn
for name, mod in [('numpy', np), ('pandas', pd), ('sklearn', sklearn),
('matplotlib', matplotlib), ('seaborn', seaborn)]:
print(f'{name}: {mod.__version__}')Freeze requirements for reproducibility
Captures the exact versions of all installed packages into requirements.txt, ensuring every collaborator or deployment uses an identical environment.
pip freeze > requirements.txt
# Share with teammates:
pip install -r requirements.txt
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