ManufacturingNet provides a sustainable, open-source ecosystem of modern artificial intelligence (AI) tools for tackling diverse engineering challenges.
Written in Python3 and designed for ease of use, ManufacturingNet's machine learning library simplifies AI for manufacturing professionals.
ManufacturingNet is developed and maintained by the Mechanical and AI Lab (MAIL) at Carnegie Mellon University.
For more information, visit our website, manufacturingnet.io.
To use ManufacturingNet, you will need a version of Python greater than 3.4 installed.
To check if Python3 is installed, open the terminal on Linux/MacOS or PowerShell on Windows and run the following command:
python3 --versionTo install ManufacturingNet and its dependencies, you will need pip, the Python package manager. If you have a version of Python greater than 3.4, pip should already be installed.
To check if pip is installed, open the terminal/PowerShell and run the following command:
pip --versionManufacturingNet depends on the following packages:
These packages will be automatically installed when you install ManufacturingNet.
The above packages should be all you need to run ManufacturingNet, but if you run into errors like ImportError: No module named ModuleName, try installing the module with pip like so:
pip install ModuleNameAfter you've installed the above requirements, open the terminal/PowerShell and run the following command:
pip install DeepManufacturingTo start using ManufacturingNet in any Python environment, import the library as such:
import ManufacturingNetIf you don't need the entire library, you can import specific classes using dot notation and "from" statements. For example, to import the linear regression model, use this code:
from ManufacturingNet.models import LinRegressionTo import the feature extraction functionality, use this code:
from ManufacturingNet.featurization import FeaturizerWhen in doubt, check the documentation!