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Top 20 Python Nltk Projects
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TextBlob
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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stocksight
Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis
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ai-chatbot-framework
A python chatbot framework with Natural Language Understanding and Artificial Intelligence.
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Watcher
Watcher - Open Source Cybersecurity Threat Hunting Platform. Developed with Django & React JS. (by Felix83000)
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teller_of_tales
Create narrated video story from book chapter using NLP, OpenAI and StableDiffusion.
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Tf-Idf_Search
A Search Engine based on the principle of TF-IDF and comparing documents in a vector space using Cosine Similarity
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lyricsavant
Lyric Savant is a data-driven User Interface that leverages the Lyrics Genius API to webscrape an artist's lyrics and display a module that includes their biographical information, a sample of their lyrics, and statistical insights regarding their vocabulary and polarity scores of their lyrics.
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News-Sense
A Streamlit app based on Python that fetches top news articles from the News API, generates a summary of each article using the OpenAI GPT-3 model, analyzes the sentiment of the article using the NLTK library, and classifies the article into different categories based on keywords.
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alternatively, could we not simply split by common characters such as newlines and periods, to split it within sentences? it would be fragile with special handling required for numbers with decimal points and probably various other edge cases, though.
there are also Python libraries meant for natural language parsing[0] that could do that task for us. I even see examples on stack overflow[1] that simply split text into sentences.
[0]: https://www.nltk.org/
TextBlob is a Python toolkit for text processing. It offers some common NLP functionalities such as part-of-speech tagging and noun phrase extraction. We’ll use TextBlob in our project to perform some quick sentiment analysis on tweets.
Project mention: Jarvis: A Voice Virtual Assistant in Python (OpenAI, ElevenLabs, Deepgram) | news.ycombinator.com | 2023-12-18There is another one (Also Jarvis) that's been around for a while and is more useful, wonder if they can combine forces? https://github.com/ggeop/Python-ai-assistant
Not sure if anyone has noticed but OpenAI now has a mobile app (I've been using the PWA all this time) and the voice assistant on there is really strong. Sounds good, fast, and seems to even run a pass on my voice before it submits the query.
Project mention: Ask HN: What Underrated Open Source Project Deserves More Recognition? | news.ycombinator.com | 2024-03-07
Project mention: Humanized conversation API without exposing that it is a response made by LLM | news.ycombinator.com | 2023-11-25
Project mention: Tranformer-based Denoising AutoEncoder for ST Unsupervised pre-training | news.ycombinator.com | 2024-02-04A new PyPI package for training sentence embedding models in just 2 lines.
The acquisition of sentence embeddings often necessitates a substantial volume of labeled data. However, in many cases and fields, labeled data is rarely accessible, and the procurement of such data is costly. In this project, we employ an unsupervised process grounded in pre-trained Transformers-based Sequential Denoising Auto-Encoder (TSDAE), introduced by the Ubiquitous Knowledge Processing Lab of Darmstadt, which can realize a performance level reaching 93.1% of in-domain supervised methodologies.
The TSDAE schema comprises two components: an encoder and a decoder. Throughout the training process, TSDAE translates tainted sentences into uniform-sized vectors, necessitating the decoder to reconstruct the original sentences utilizing this sentence embedding. For good reconstruction quality, the semantics must be captured well in the sentence embeddings from the encoder. Subsequently, during inference, the encoder is solely utilized to form sentence embeddings.
GitHub : https://github.com/louisbrulenaudet/tsdae
Installation :
Project mention: Making sense of the news with GPT-3, NLTK, Python and Streamlit | dev.to | 2023-07-18You can find the code for News 📰 Sense and instructions to use it at https://github.com/tanmaychk/News-Sense. Before starting, make sure you have the following:
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Index
What are some of the best open-source Nltk projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | NLTK | 13,054 |
2 | TextBlob | 8,956 |
3 | stocksight | 2,004 |
4 | ai-chatbot-framework | 1,917 |
5 | rake-nltk | 1,034 |
6 | Python-ai-assistant | 859 |
7 | cltk | 820 |
8 | Watcher | 797 |
9 | bibaandboba | 136 |
10 | orange3-text | 124 |
11 | Sentiment-analysis-of-financial-news-data | 118 |
12 | dialog | 57 |
13 | twitter-stock-sentiment | 9 |
14 | anime_wordclouds | 8 |
15 | teller_of_tales | 6 |
16 | Precis | 3 |
17 | tsdae | 3 |
18 | Tf-Idf_Search | 2 |
19 | lyricsavant | 1 |
20 | News-Sense | 0 |
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