AI and Time Series Data: Harnessing the Power of Temporal Insights

1. examples

   1 177 8,144 6.9 Jupyter Notebook

   TensorFlow examples (by tensorflow)

   

   As we prepare for the next phase in AI evolution, embracing decentralized approaches and synthetic data generation will be essential. Developers are encouraged to explore technologies like TensorFlow, Prophet, and platforms hosted on Ocean Protocol and License Token for further exploration. Additionally, more detailed discussions on these topics can be found in in-depth Dev.to posts such as Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models.

2. Stream

   getstream.io featured

   Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.

   

3. octl

   2 40 8 6.8 Solidity

   Sourcecode, Examples, Howtos

   

   As we prepare for the next phase in AI evolution, embracing decentralized approaches and synthetic data generation will be essential. Developers are encouraged to explore technologies like TensorFlow, Prophet, and platforms hosted on Ocean Protocol and License Token for further exploration. Additionally, more detailed discussions on these topics can be found in in-depth Dev.to posts such as Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models.

4. ocean.py

   3 18 173 2.6 Python

   🦑 Ocean Protocol's Python library to privately & securely publish, exchange, and consume data.

   

   Data NFT Monetization: Tokenize curated time series datasets through platforms like Ocean Protocol or License Token, creating decentralized market opportunities for AI training data.

5. Prophet

   4 225 19,384 7.1 Python

   Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

   

   As we prepare for the next phase in AI evolution, embracing decentralized approaches and synthetic data generation will be essential. Developers are encouraged to explore technologies like TensorFlow, Prophet, and platforms hosted on Ocean Protocol and License Token for further exploration. Additionally, more detailed discussions on these topics can be found in in-depth Dev.to posts such as Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models.

6. nixtla

   5 12 2,834 8.8 Jupyter Notebook

   TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

   

   AI techniques like Long Short-Term Memory (LSTM) networks and transformer-based architectures are now common in time series forecasting. Models like TimeGPT are trained on billions of data points, facilitating zero-shot prediction across multiple domains. In parallel, emerging blockchain-driven technologies enable the tokenization and monetization of time series datasets via Data NFTs, creating secure digital marketplaces for data.

7. InfluxDB

   www.influxdata.com featured

   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

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