xfer
Transfer Learning library for Deep Neural Networks. (by amzn)
gensim
Topic Modelling for Humans (by piskvorky)
xfer | gensim | |
---|---|---|
1 | 18 | |
250 | 15,256 | |
0.0% | 0.7% | |
0.0 | 7.5 | |
10 months ago | 8 days ago | |
Python | Python | |
Apache License 2.0 | GNU Lesser General Public License v3.0 only |
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.
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.
xfer
Posts with mentions or reviews of xfer.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[R] Fast Adaptation with Linearized Neural Networks
Abstract: The inductive biases of trained neural networks are difficult to understand and, consequently, to adapt to new settings. We study the inductive biases of linearizations of neural networks, which we show to be surprisingly good summaries of the full network functions. Inspired by this finding, we propose a technique for embedding these inductive biases into Gaussian processes through a kernel designed from the Jacobian of the network. In this setting, domain adaptation takes the form of interpretable posterior inference, with accompanying uncertainty estimation. This inference is analytic and free of local optima issues found in standard techniques such as fine-tuning neural network weights to a new task. We develop significant computational speed-ups based on matrix multiplies, including a novel implementation for scalable Fisher vector products. Our experiments on both image classification and regression demonstrate the promise and convenience of this framework for transfer learning, compared to neural network fine-tuning. Code is available at this https URL.
gensim
Posts with mentions or reviews of gensim.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-23.
- Aggregating news from different sources
-
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. 🤝
-
Topic modeling --- allow multiple topics per statement
Try LDA as implemented in gemsin https://github.com/RaRe-Technologies/gensim
-
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
-
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;
-
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...
-
[Research] Text summarization using Python, that can run on Android devices?
TextRank will work without any problems. https://radimrehurek.com/gensim/
-
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.