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Machine Learning on Browser using TensorFlow.js
This is about to change, not all machine learning problem are big require heavy compute powers, some of them could be solved by processing power of the browsers. TensorFlow.js comes to help us here.
- Not all machine learning problems require high-end computation and solutions
- Some of the machine learning problems can be solved in UI layer
Covers both low-level & high-level machine learning
- What is the difference between this classification
- When to use which approach
API to consume pre-trained models
- Explanation on the need for APIs and how to consume Kera models in TensorFlow.js
Examples of Machine learning (data)
Example of Machine learning on image recognition
- Discuss an example of image recognition to extract data from images with pre-trained model
Adoption & Future in store
- Performance of the TensorFlow.js in browser is 1.5X (smaller model) to 15X (huge data sets) againts TensorFlow in Python. So, use is judiacially
- TensorFlow.js is not supported in Node.js yet, but we can expect the support in near future due to popularity of Node.js
- Great fit for simple machine learning use case which can be solved in UI client side
- no specific requirement -
Girimurugan has 15 years of experience in enterprise software development. Has worked with SAP for more than a decade on various web applications and currently contributes for WalmartLabs in Bangalore. Girimurugan has extensive experience on developing & designing web application of enterprise scale. He is currently focusing on solving enterprise problems with Conversational User Experience & Machine Learning.