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Is Javascript Good For Machine Learning?
Can I do Machine Learning with JavaScript?
The short answer is yes.
I did some research here are the findings
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#100DaysOfCode #javascript #CodeNewbies
Can I do Machine Learning with JavaScript?
The short answer is yes.
I did some research here are the findings
Thread
#100DaysOfCode #javascript #CodeNewbies
Few things that are said about JavaScript when it comes to Machine Learning.
- Javascript is slow.
- Handling Matrices is difficult with JavaScript.
- Python got all the major libraries.
- Javascript is slow.
- Handling Matrices is difficult with JavaScript.
- Python got all the major libraries.
Python got all the major libraries
Yes. all the important libraries for M.L. in which much of the study and research has been done, are made in Python.
For e.g.
TensorFlow and scikit-learn.
Yes. all the important libraries for M.L. in which much of the study and research has been done, are made in Python.
For e.g.
TensorFlow and scikit-learn.
But that doesn't let you find good options like
- brain.js for neural networks.
- Natural for natural language processing.
- TensorflowJs for model training
- Webdnn for deep learning.
- brain.js for neural networks.
- Natural for natural language processing.
- TensorflowJs for model training
- Webdnn for deep learning.
What is possible with Machine Learning and JavaScript?
Many developers are moving from handling ML on back-end servers to front-end applications.
TensorFlow.js, teams can now create and run ML models in static HTML documents without ever setting up a server or even database.
Many developers are moving from handling ML on back-end servers to front-end applications.
TensorFlow.js, teams can now create and run ML models in static HTML documents without ever setting up a server or even database.
1. Automatic Picture Manipulation:
Auto-adjust images based on a predefined rule-set using a browser-based application — even generate art using convolutional neural networks, as Google has done.
Auto-adjust images based on a predefined rule-set using a browser-based application — even generate art using convolutional neural networks, as Google has done.
2. Offline Game Opponents:
Play against an AI-operated adversary, even when a video game is offline.
3. Activity Monitoring:
Install a client-side application that learns usage patterns on a local network or device — to monitor and flag unusual activity.
Play against an AI-operated adversary, even when a video game is offline.
3. Activity Monitoring:
Install a client-side application that learns usage patterns on a local network or device — to monitor and flag unusual activity.
4. Content Recommendation Engine:
Build and train an ML algorithm in the browser, identifying what users like to look at and surfacing more relevant content — just as Twitter has done to rank tweets.
Build and train an ML algorithm in the browser, identifying what users like to look at and surfacing more relevant content — just as Twitter has done to rank tweets.
5. Object Detection:
Use a client-side application to detect documents or objects in pictures — such as Airbnb uses to alert users to the presence of sensitive information when they upload a passport or driving license photo.
JavaScript for ML will grow in future
Use a client-side application to detect documents or objects in pictures — such as Airbnb uses to alert users to the presence of sensitive information when they upload a passport or driving license photo.
JavaScript for ML will grow in future
