torchextractor VS stringlifier

Compare torchextractor vs stringlifier and see what are their differences.

stringlifier

Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data. (by adobe)
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torchextractor stringlifier
1 1
99 157
- 0.0%
4.2 0.0
about 3 years ago about 1 year ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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torchextractor

Posts with mentions or reviews of torchextractor. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-11.
  • [P] Pytorch: Intermediate Feature Extraction
    2 projects | /r/MachineLearning | 11 Mar 2021
    Recently I worked on torchextrator, a standalone python package that makes it simple to extract features in PyTorch. You no longer need to duplicate code and rewrite the forward function. Also the extractor supports nested modules, custom caching operations and is ONNX compatible!

stringlifier

Posts with mentions or reviews of stringlifier. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing torchextractor and stringlifier you can also consider the following projects:

muzero-general - MuZero

pyDenStream - Implementation of the DenStream algorithm in Python.

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

PolyFuzz - Fuzzy string matching, grouping, and evaluation.

merged_depth - Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

carbon - :black_heart: Create and share beautiful images of your source code

DBCV - Python implementation of Density-Based Clustering Validation

Unredactor - In this project we are tryinbg to create unredactor. Unredactor will take a redacted document and the redacted flag as input, inreturn it will give the most likely candidates to fill in redacted location. In this project we are only considered about unredacting names only. The data that we are considering is imdb data set with many review files. These files are used to buils corpora for finding tfidf score. Few files are used to train and in these files names are redacted and written into redacted folder. These redacted files are used for testing and different classification models are built to predict the probabilies of each class. Top 5 classes i.e names similar to the test features are written at the end of text in unreddacted foleder.

woodKubernetes - LXD wood cluster

mapextrackt - Pytorch Feature Map Extractor

richkit - Domain Enrichment Toolkit $ pip install richkit