android-bootstrap
great_expectations
Our great sponsors
android-bootstrap | great_expectations | |
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21 | 15 | |
60 | 9,440 | |
- | 1.7% | |
1.8 | 9.9 | |
about 3 years ago | 6 days ago | |
Kotlin | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
android-bootstrap
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Build end-to-end AI Apps in minutes using just your phone.
This is interesting. The closest I can compare it to is lobe.ai.
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When is Lobe Image Classifying coming
lobe.ai says object detection is coming soon
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lobe.ai. new version
I need urgent help please!!! I've just installed the new Version of lobe.ai on my MAC and now, after it has finished, the prediction rate has decreased from more than 90% to 50% :-( :-(
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Camera Works for "Label" But Not for "Use"
Using lobe.ai 0.10.1130.5 I successfully trained using my Webcam Logitech C920. The camera turned live, and I could take individual and rapid-snap photos. But after proceeding to 'Use', the camera button does show, but nothing happens when I press it, not does hovering raise a floating menu. What am I doing wrong?
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Rasp Pi OS Bullseye has dropped support of PiCamera - breaks Lobe on Rasp P
Found a fix here? There is some bugs in the lobe.ai code:
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Problem getting Lobe.io on Android Device with Android Studio
There is this android-bootstrap https://github.com/lobe/android-bootstrap. In that "getting started" I did everything but I feel like there are steps missing between 4 and 5. The "Run" button is grayed-out.
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can't deploy lobe ai web
I can run the lobe.ai web version locally.
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Anyone have examples of great website copy for a SAAS product?
lobe.ai
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Android no metadata found for tflite model
Are you copying both the saved_model.tflite model and signature.json files? https://github.com/lobe/android-bootstrap#get-started
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[UPDATE] My Isaac Item Recogniser app in action. Only Android version for now, beta test soon ;)
I have no plans on open sourcing my app, but here are bits and pieces I used to build upon :)
great_expectations
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Data Quality at Scale with Great Expectations, Spark, and Airflow on EMR
Great Expectations (GE) is an open-source data validation tool that helps ensure data quality.
- Looking for Unit Testing framework in Database Migration Process
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Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
GE is arguably the most well known OSS alternative to Soda Core. The third option is deequ, originally developed and released in OSS by AWS. Our community has told us that Soda Core is different because itβs easy to get going and embed into data pipelines. And it also allows some of the check authoring work to be moved to other members of the data team. I'm sure there are also scenarios where Soda Core is not the best option. For example, when you only use Pandas dataframes or develop in Scala.
- Greatexpectations - Always know what to expect from your data.
- Greatexpectations β Always know what to expect from your data
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Package for drift detection
great_expectations: https://github.com/great-expectations/great_expectations
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[D] Do you use data engineering pipelines for real life projects?
For example I just found "Great Expectations" and "Kedro", "Flyte" and I was wondering at which point in time and project complexity should we choose one of these tools instead of the ancient cave man way?
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Data pipeline suggestions
Testing: GreatExpectations
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
- [P] Deepchecks: an open-source tool for high standards validations for ML models and data.
What are some alternatives?
streamlit - Streamlit β A faster way to build and share data apps.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
kedro-great - The easiest way to integrate Kedro and Great Expectations
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
cld3-kotlin - Bindings to Google's Compact Language Detector 3 to JVM Based Languages
re_data - re_data - fix data issues before your users & CEO would discover them π
metaflow - Build and manage real-life data science projects with ease.
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models