We are excited to announce the launch of ModelChimp 0.2. A new and improved ModelChimp that helps ML engineers track experiments, collaborate and analyze results with only a few lines of code.
What makes ModelChimp 0.2 special?
Revamped UI: All new and updated UI built with React.
Jupyter Integration: Jupyter is now a popular amongst data scientists and ML Engineers because of it's versatile interactive coding environment for exploring code and data. With ModelChimp integrated into Jupyter notebooks keeping track of your experiments are just a few lines of code away.
Did you know: In the past year, the number of ipynb files on GitHub has nearly tripled from 80,000 to over 230,000 files.
Grid Search: The traditional way of performing hyperparameter optimization has been grid search, or a parameter sweep, which is simply an exhaustive search through a manually specified subset of the hyperparameters. With the grid search embedded into ModelChimp, finding the right subset of hyperparameters is just a graph away.
Try ModelChimp with your Jupyter Notebook:
Sign up on the Modelchimp site and get started with this Jupyter notebook below.
MNIST ("Modified National Institute of Standards and Technology") is the de facto “hello world” dataset of computer vision. Our goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.
If you've got suggestions or improvements for the product you can reach out to me on firstname.lastname@example.org.