yahoo-oauth VS TensorFlowOnSpark

Compare yahoo-oauth vs TensorFlowOnSpark and see what are their differences.

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yahoo-oauth TensorFlowOnSpark
1 2
64 3,864
- 0.1%
10.0 1.4
over 1 year ago 10 months ago
Python Python
MIT 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.

yahoo-oauth

Posts with mentions or reviews of yahoo-oauth. We have used some of these posts to build our list of alternatives and similar projects.
  • Has anyone successfully connected to the Yahoo API through their PHP example?
    1 project | /r/fantasyfootballcoding | 9 Sep 2022
    Honestly, their documentation hasn't been updated since god knows when, so it's not surprising to me that their code is broken. Is there any way you can use Python to make the initial handshake and get your access tokens? I ask because if you have that then the rest might work as intended. Maybe look through this library to see if there's anything you can use or help diagnose the issue? (https://github.com/josuebrunel/yahoo-oauth)

TensorFlowOnSpark

Posts with mentions or reviews of TensorFlowOnSpark. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-03.

What are some alternatives?

When comparing yahoo-oauth and TensorFlowOnSpark you can also consider the following projects:

PSS - Pi-hole SafeSearch (PSS)

ecosystem - Integration of TensorFlow with other open-source frameworks

Search Engine Parser - Lightweight package to query popular search engines and scrape for result titles, links and descriptions

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Keras - Deep Learning for humans

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.

mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.