pyvtreat vs keras

pyvtreat

vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under a BSD-3-Clause license. (by WinVector)

Source Code

winvector.github.io

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keras

Deep Learning for humans [Moved to: https://github.com/keras-team/keras] (by fchollet)

Deep Learning Tensorflow neural-networks Machine Learning Data Science Python

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pyvtreat		keras
	Project
1	Mentions	3
114	Stars	54,926
0.0%	Growth	-
6.9	Activity	9.9
7 months ago	Latest Commit	about 2 years ago
Python	Language	Python
GNU General Public License v3.0 or later	License	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.
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.

pyvtreat

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

Tidying up Pipelines with DataClasses
1 project | dev.to | 11 Nov 2020

Handle the categorical columns using the vtreat package

keras

Posts with mentions or reviews of keras. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-13.

Keras - Difference between categorical_accuracy and sparse_categorical_accuracy
1 project | /r/codehunter | 5 May 2022

The source code can be found here:
keras error on predict
1 project | /r/codehunter | 18 Apr 2022

Here
How to get reproducible results in keras
2 projects | /r/codehunter | 13 Apr 2022

I get different results (test accuracy) every time I run the imdb_lstm.py example from Keras framework (https://github.com/fchollet/keras/blob/master/examples/imdb_lstm.py)The code contains np.random.seed(1337) in the top, before any keras imports. It should prevent it from generating different numbers for every run. What am I missing?

What are some alternatives?

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auton-survival - Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

InceptionTime - InceptionTime: Finding AlexNet for Time Series Classification

watermark-removal - a machine learning image inpainting task that instinctively removes watermarks from image indistinguishable from the ground truth image

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

TFLearn - Deep learning library featuring a higher-level API for TensorFlow.

seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow