Detailed release notes for the Engine
We are proud to showcase the incredible work the team has accomplished in this release - version 1.5.0! We had two primary objectives for this release:
- Improve functionality of Data Import & make recipe-building optional; that is, if users already have clean data, they can just upload it to the Engine and jump straight into training models. To make this possible, we had to completely rethink how to handle the new dataset creation process.
- Overhaul the Engine's user interface and user experience; we witnessed users' troubles in navigating our platform and invested our efforts into making sure the navigation hierarchy is consistent and logical. We've also added suitable onboarding assistance to guide the user through their AI journey.
Data Import improvements
1. New dataset creation process
Previously, when users imported data to the Engine, it was automatically read and stored as text format if the schema was not provided by the data source. This approach had 2 drawbacks:
- The user has no flexibility in changing the configurations for reading their file/data.
- The user is forced to create a recipe to change the column datatype in their dataset.
To address this, we added 2 more steps to the new dataset creation process:
Let's look at Steps 3 and 4:
Configure - Step 3 of the process
For file upload, the Engine automatically detects the proper configurations for reading the file. In addition to that, we also provide users with the flexibility to change the configurations as necessary.
Confirm Schema - Step 4 of the process
Here, users can change the column names and datatype for their dataset.
2. Improved HTTP process
The new HTTP import process now shows the user, the importing process on the GUI before proceeding further to create the new dataset.
3. Excel support for file upload
Now, users can upload Excel files to the Engine to create their dataset. Users can specify the worksheets to include, and the Engine will automatically detect the range of the data to extract. As always, users have the flexibility to manually configure the data range.
4. Query capability for Databases
When importing data from databases, users are no longer restricted to just extracting a single data table/collection. They can now specify a query when importing data from databases - allowing users to specifically extract their desired data and removing the need to use a recipe in achieving the same result.
New Engine user interface & experience
1. Guided tour for first-time users
When entering the Engine for the first time, there will be a guided tour with onboarding cards to orient the user around the homepage.
2. New Homepage
Instead of the flowchart navigation as the homepage, projects are now front-and-centre in the homepage (and rightfully so). In the Engine, projects are like spaces or folders, in which users can start building their own Machine Learning models.
Note: For new trial users, the Engine will automatically create "Your first project" for you.
3. New Project-level navigation
We have also abandoned the contextual navigation in the old design, in favour of a persistent navigation in the left panel within the Project-level view. This will provide constant clarity to users as to where they currently are within the project.
In addition, we have also added guided steps at both the project and app pages, so users are clear on the next steps to take in their AI journey.
Apart from these major changes, the team has also made several minor improvements to the UI/UX, but I will leave it to users to experience it for themselves.
Communicate with PI.EXCHANGE team
At PI.EXCHANGE, our top priority is to better serve our users. To achieve this, we need to provide avenues for you to provide us with your feedback. Here, we added the ability for users to:
Give feedback to the team, whether it be positive or negative
Report an issue encountered in the Engine
At PI.EXCHANGE, we are on a constant quest to better serve our users. If you have a feature request, let us know here. We would love to hear from you.
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