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Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables | It is a cutting-edge open-source solution that streamlines the process of finding information in the project documentation. With its integration of the powerful GPT models, developers can easily ask questions about a project and receive accurate answers. |
Classification & Anomaly Detection- With our machine learning algorithms and your time series data, we can get up to 99% prediction accuracy on the state of the sensor. Algorithms include neural network, random forest, support vector machine and others.;Streaming Data Infrastructure- We provide the infrastructure for your streaming data as a service including a highly scalable time-series database and analytics capabilities.;Analytics Across All Your Devices- Capture and aggregate data from all of your devices to perform analytics across the entire dataset.;Random Forest, SVM, Decision Tree, Node.js, Streaming Data | Have interactive conversations and find answers based on the provided data;
Built on open source principles, promoting transparency and collaboration;
Eliminate lengthy manual searches;
Trust that your data is kept safe and confidential |
Statistics | |
GitHub Stars - | GitHub Stars 17.3K |
GitHub Forks - | GitHub Forks 1.9K |
Stacks 48 | Stacks 1 |
Followers 77 | Followers 4 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.

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Is a training API for researchers and developers.

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