cape-dataframes
private-ai
Our great sponsors
| cape-dataframes | private-ai | |
|---|---|---|
| 4 | 2 | |
| 174 | 4 | |
| 0.0% | - | |
| 0.0 | 10.0 | |
| 9 months ago | over 4 years ago | |
| Python | Jupyter Notebook | |
| 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.
cape-dataframes
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Show HN: Cape API – Keep your sensitive data private while using GPT-4
- How can we mitigate hallucinations and bias so that we have higher trust in AI generated text?
The features of the Cape API are designed to help solve these problems for developers, and we have a number of early customers using the API in production already.
To get started, checkout our docs: https://docs.capeprivacy.com/
View the API reference: https://api.capeprivacy.com/redoc
Join the discussion on our Discord: https://discord.gg/nQW7YxUYjh
And of course try the CapeChat playground at https://chat.capeprivacy.com/
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Secure Sentiment Analysis with Enclaves
There are three essential components that enable this: cape encrypt, cape deploy, and cape run. The command cape encrypt encrypts inputs that can be sent into the Cape enclave for processing, cape deploy performs all needed actions for deploying a function into the enclave, and finally cape run invokes the deployed function with an input that was previously encrypted with cape encrypt. Learn more on the Cape docs.
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Anonymize your Data with a single line!
Well, many of the features in this project are simply wrappers around other libraries like this one. Therefore, the value proposition of this project would either have to be the automation aspect or the idea that you can shield the user from the details of how the implemented techniques work. I think both approaches are risky in this setting.
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Data Anonymization Libraries
I was wondering what other helpful and easy of use libraries are there for data anonymization like faker and cape-python ?
private-ai
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Show HN: Cape API – Keep your sensitive data private while using GPT-4
Something like https://github.com/microsoft/presidio for stripping out PII might fill the role I expected https://github.com/capeprivacy/private-ai to do.
What are some alternatives?
popmon - Monitor the stability of a Pandas or Spark dataframe ⚙︎
presidio - Context aware, pluggable and customizable data protection and de-identification SDK for text and images
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
koalas - Koalas: pandas API on Apache Spark
exodus - Platform to audit trackers used by Android application
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
dvc - 🦉 ML Experiments and Data Management with Git
open-data-anonimizer - Python Data Anonymization & Masking Library For Data Science Tasks [Moved to: https://github.com/ArtLabss/open-data-anonymizer]
pycape - The Cape Privacy Python SDK
cape-js - The Cape Privacy JavaScript SDK
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.