Open Source Solutions for Machine Learning Engineers

Our Open Source community is focused in developing tools that make the Machine Learning work faster, easier, and reproducible. Join our effort in democratizing AI and creating tools that empower engineers to disrupt industries. Check us out onGithub!

Join the effort!

Download, install, and use our tools to make your work easier. Then, make improvements and submit a pull request! We're eager to see what you have to add!

Stripping

If you ever wanted to have Jupyter's benefits without using Jupyter, this is where you'll start. Stripping enables you to run plain Python code that is fully compatible with version control systems such as git, allowing for collaboration with the speed and flexibility that a Jupyter session affords you.
from stripping import setup_stripping
st, c = setup_stripping('.stripping')

@st.step()
def load_dataset():
    c.bf_file = join("datasets", "dataset.csv")
    c.bf = pd.read_csv(c.bf_file)

Aurum

Worth its weight in gold, Aurum automatically keeps track of all your experiments and its performance along with the details about the dataset version while giving you the ability to export any experiment straight out of your terminal or github. Now, that's some mad skills.
import aurum as au
au.use_datasets("dataset.csv")
au.parameters(test_size=0.15,
              random_state=0,
              n_estimators=1000)