stanford-tensorflow-tutorials
stanford-openie-python
| stanford-tensorflow-tutorials | stanford-openie-python | |
|---|---|---|
| 2 | 1 | |
| 9,845 | 629 | |
| - | - | |
| 0.0 | 4.3 | |
| over 3 years ago | 8 months ago | |
| Python | Python | |
| MIT License | ISC License |
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stanford-tensorflow-tutorials
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Rim Dillon
I’m not sure how to tell you this in a way that won’t deflate your outrage boner, but Stanford uses master in code: https://github.com/chiphuyen/stanford-tensorflow-tutorials
- [D] I'm trying to do more stuff in pure Tensorflow. Is there an in-depth book that explain constructing recurrent, convolutional, graph etc layers in it?
stanford-openie-python
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“[Project]” Manual Annotation Tool for Relation Extraction
What would your relation look like? If it going to be rather abstract like a relation in a knowledge base (e.g., per:child_of)? Or is it okay if it's more free form? If it's the latter then I'd recommend looking at open information extraction tools. There's a Python implementation of Stanford's OpenIE system from 2015 here and there are other works that have open-sourced their code.
What are some alternatives?
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
baresipy - baresip python wrapper
DeepDanbooru - AI based multi-label girl image classification system, implemented by using TensorFlow.
python-sutime - Python wrapper for Stanford CoreNLP's SUTime
leetcode-compensation - Compensation analysis of leetcode.com/discuss/compensation.
unrpa - A program to extract files from the RPA archive format.
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
ddb-extraction - Extract the samples of a DDB Vocaloid file.
ChatterBot - ChatterBot is a machine learning, conversational dialog engine for creating chat bots
reddit-karma-farming-bot - "Is karma really that important to you? Damn bro, you need a life" - YouTube Comment
jina - ☁️ Build multimodal AI applications with cloud-native stack
python-minecraft-clone - Source code for each episode of my Minecraft clone in Python YouTube tutorial series.