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Top 5 Jupyter Notebook feature-extraction Projects
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Deep_Learning_Machine_Learning_Stock
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
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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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NLP-CNN-Subreddit-Sorter-Heroku-App
End-to-end development of an application using a convolutional neural network that suggests to users/moderators which technical subreddit a post actually belongs to. Novel method to determine # of CNN filters. Custom Word2vec embeddings. The subreddits chosen are all technical and similar, and benefit users/moderators interested in data science and related fields. (Exploratory data analysis, feature engineering, custom word2vec embeddings, convolutional neural network, deployment via flask to
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
Project mention: For deep learning practitioners in industry, is the workflow always this annoying? [D] | /r/MachineLearning | 2023-07-10This is definitely a good thing to try for time-series; you can automate your feature extraction too (eg using https://github.com/blue-yonder/tsfresh ).
Project mention: Deep_Learning_Machine_Learning_Stock: NEW Deep Learning And Reinforcement Learning - star count:1017.0 | /r/algoprojects | 2023-12-10
While there are abundant researches about evaluating ChatGPT on natural language understanding and generation tasks, few studies have investigated how ChatGPT's behavior changes over time. In this paper, we collect a coarse-to-fine temporal dataset called ChatLog, consisting of two parts that update monthly and daily: ChatLog-Monthly is a dataset of 38,730 question-answer pairs collected every month including questions from both the reasoning and classification tasks. ChatLog-Daily, on the other hand, consists of ChatGPT's responses to 1000 identical questions for long-form generation every day. We conduct comprehensive automatic and human evaluation to provide the evidence for the existence of ChatGPT evolving patterns. We further analyze the unchanged characteristics of ChatGPT over time by extracting its knowledge and linguistic features. We find some stable features to improve the robustness of a RoBERTa-based detector on new versions of ChatGPT. We will continuously maintain our project at https://github.com/THU-KEG/ChatLog.
Jupyter Notebook feature-extraction related posts
- For deep learning practitioners in industry, is the workflow always this annoying? [D]
- [D] Incorporating external data in LSTM models for sales forecasting in e-commerce
- [R] Approach to identify clusters on a time series
- The outputs of my jupyter notebooks inside of Github repos only show half of what they used to. Why did this happen and how to fix? I am certain that the outputs used to show everything when viewed in Github, and I have not reuploaded the notebooks to the repo's since then.
- The outputs of my jupyter notebooks inside of Github repos only show half of what they used to. Why did this happen and how to fix? I am certain that the outputs used to show everything when viewed in Github.
- The outputs of my jupyter notebooks inside of Github repos only show half of what they used to. Why did this happen and how to fix? I am certain that the outputs used to show everything when viewed in Github.
- Automatic time series feature extraction based on scalable hypothesis tests
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A note from our sponsor - WorkOS
workos.com | 19 Apr 2024
Index
What are some of the best open-source feature-extraction projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | tsfresh | 8,068 |
2 | Deep_Learning_Machine_Learning_Stock | 1,139 |
3 | deltapy | 527 |
4 | ChatLog | 93 |
5 | NLP-CNN-Subreddit-Sorter-Heroku-App | 1 |