Welcome to the Treehouse Community
Want to collaborate on code errors? Have bugs you need feedback on? Looking for an extra set of eyes on your latest project? Get support with fellow developers, designers, and programmers of all backgrounds and skill levels here with the Treehouse Community! While you're at it, check out some resources Treehouse students have shared here.
Looking to learn something new?
Treehouse offers a seven day free trial for new students. Get access to thousands of hours of content and join thousands of Treehouse students and alumni in the community today.
Start your free trial
Routine Poutine
26,050 PointsIs TensorFlow.js worth getting into as a JavaScript developer?
Would you recommend using JavaScript for machine learning and AI, or limiting JavaScript to web development and adding Python for the latter? Maybe I am looking at this wrong, because I am also wondering... if the reason we should add machine learning to JavaScript is to make websites capable of analyzing data seamlessly. Would it be possible to create a site with JavaScript in the browser and Nodejs environment, and successfully add machine learning components?
The only guy I know working on AI does not know JavaScript. He knows Java, R, Julia, and probably Python.
1 Answer
Eric M
11,545 PointsWhile I haven't used TensorFlow I do have a bit of experience switching problem domains and languages at the same time.
It will probably be easier to pick up TensorFlow using a language you already know than to switch to another language because it's "better" for the problem space and then need to learn a new language and a new domain at the same time.
That said, "analysing data seamlessly" does not tell me anything about what you actually want to achieve other than you want it to be fast. Depending on the data - and what you mean by analyse, this could be accomplished without using machine learning. Every programming language does something with data - almost every program can be described as organising, collecting, or doing something useful with data.
As to how seamless it is, and what tools and techniques work best, it depends on what you're trying to do.
If the data your dealing with is not immense in scope, and if you can describe the relationship between different data points, you might get further faster with a relational database and a good JavaScript charting library.
If you're doing image analysis - which is a good machine learning case - then check out AWS Rekognition (I believe you can use it a little on the free tier) which provides a simple REST API into an existing image analysis model. It's especially good for face recognition but can do many objects and scenes as well.
Either way playing around with Rekognition might give you an idea of one way you can implement a web frontend that passes data to and from an analysis engine.