Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
JS Tigers can help you implement Machine Learning for your applications using TensorFlow.js.
TensorFlow.js has become one of the most popular Machine Learning JavaScript projects due to its comprehensive linear algebra core and deep learning layers. It is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. TenserFlow.js can be used to
- Develop ML in the Browser: Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.
- Develop ML in Node.js environment: Execute native TensorFlow with the same TensorFlow.js API under the Node.js runtime.
- Run Existing models: Use TensorFlow.js model converters to run pre-existing TensorFlow models right in the browser.
- Retrain Existing models: Retrain pre-existing ML models using sensor data connected to the browser or other client-side data.