leetcode-compensation
gensim
| leetcode-compensation | gensim | |
|---|---|---|
| 1 | 18 | |
| 111 | 15,256 | |
| - | 0.9% | |
| 0.0 | 7.5 | |
| almost 2 years ago | 9 days ago | |
| Python | Python | |
| - | GNU Lesser General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
leetcode-compensation
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Leetcode Total Compensation report (India) 5th Jan 2019 - 5th Aug 2021
- Show some ❤️ if you find it useful - https://github.com/urk-stav/leetcode-compensation
gensim
- Aggregating news from different sources
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Understanding How Dynamic node2vec Works on Streaming Data
This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝
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Topic modeling --- allow multiple topics per statement
Try LDA as implemented in gemsin https://github.com/RaRe-Technologies/gensim
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Is it home bias or is data wrangling for machine learning in python much less intuitive and much more burdensome than in R?
Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling.
- sentence transformer vector dimensionality reduction to 1
- Where to start for recommendation systems
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GET STARTED WITH TOPIC MODELLING USING GENSIM IN NLP
Here we have to install the gensim library in a jupyter notebook to be able to use it in our project, consider the code below;
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Show HN: I built a site that summarizes articles and PDFs using NLP
Nice work! I wonder if you're going the same challenges that gensim had for being generic in summarization.
For context:
> Despite its general-sounding name, the module will not satisfy the majority of use cases in production and is likely to waste people's time.
https://github.com/RaRe-Technologies/gensim/wiki/Migrating-f...
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[Research] Text summarization using Python, that can run on Android devices?
TextRank will work without any problems. https://radimrehurek.com/gensim/
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Topic modelling with Gensim and SpaCy on startup news
For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use.
What are some alternatives?
stanford-tensorflow-tutorials - This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
autoscraper - A Smart, Automatic, Fast and Lightweight Web Scraper for Python
scikit-learn - scikit-learn: machine learning in Python
jina - ☁️ Build multimodal AI applications with cloud-native stack
MLflow - Open source platform for the machine learning lifecycle
portfoliomanager - Track financial goals using contributions to Shares, Restricted Stock Units, Employee Stock Purchase Plan, 401K, Gold, Crypto, Provident Fund, Sukanya Samriddhi, Mutual Funds
tensorflow - An Open Source Machine Learning Framework for Everyone
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
Keras - Deep Learning for humans
sbi-tt-rates-historical - Historical SBI TT rates since 02 July 2020. These are one of important rates required for ITR purposes and not made readily available by RBI/SBI unfortunately.
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)