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docs: fix typos in README.md [skip ci] #2699

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Dec 6, 2023
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docs: fix typos in README.md [skip ci] #2699

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docs: fix typos in README.md [skip ci]
eyal352 Nov 22, 2023
28f5e60
Merge branch 'main' into fix-readme-typos
harsh-deepchecks Dec 5, 2023
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8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -112,7 +112,7 @@ pip install deepchecks-installer
deepchecks-installer install-monitoring
```

This will automatically download the necessary dependencies, run the installation prcoess
This will automatically download the necessary dependencies, run the installation process
and then start the application locally.

The installation will take a few minutes. Then you can open the deployment url (default is http://localhost),
Expand Down Expand Up @@ -218,7 +218,7 @@ At its core, Deepchecks has a wide variety of built-in Checks and Suites (lists
for all data types (Tabular, NLP, Vision),
These includes checks for validating your model's performance (e.g. identify weak segments), the data's
distribution (e.g. detect drifts or leakages), data integrity (e.g. find conflicting labels) and more.
These checks results can be run manually (e.g. during research) or trigerred automatically (e.g. during CI
These checks results can be run manually (e.g. during research) or triggered automatically (e.g. during CI
and production monitoring) and enable automatically making informed decisions regarding your model pipelines'
production-readiness, and behavior over time.
--->
Expand All @@ -233,7 +233,7 @@ production-readiness, and behavior over time.

- All of the Checks and the framework for customizing them are implemented inside
the Deepchecks Testing Python package (this repo).
- Each check tests for a specific potential problem. Deepchecks has many preimplemented checks for
- Each check tests for a specific potential problem. Deepchecks has many pre-implemented checks for
finding issues with the model's performance (e.g. identifying weak segments),
data distribution (e.g. detect drifts or leakages) and data integrity (e.g. find conflicting labels).
- Customizable: each check has many configurable parameters, and custom checks can easily be implemented.
Expand All @@ -253,7 +253,7 @@ production-readiness, and behavior over time.
<!---
These checks can be run manually (e.g. during research) or automatically triggered (with CI processes or in scheduled runs for production monitoring).
The check's results can be examined with visual reports (by saving them to an HTML file, or seeing them in Jupyter),
processed with code (using their json output), and inspected and colloaborated upon with a dynamic UI
processed with code (using their json output), and inspected and collaborated upon with a dynamic UI
(for examining test results and for production monitoring).
Optional conditions can be added to each check, to automatically validate whether it passed or not.
--->
Expand Down