Can a machine really learn and think...can it really answer all my questions from spelling correction to voice prediction or even in the financial aspect that whether it's a promising stock market or otherwise?
The answer is YES! But if a machine can; so does human, the gulf of the difference comes while comparing the efficiency and the response time which is our basic purpose for an entirely automatized world where everything works on tick of a clock.
Now the next question comes if our machines can already take decisions for us, how we can make it more efficient and interactive? The answer is deeplearn.js which is an initiative from Google Brain PAIR for the browser to redesign the human interactions with ML. You can use the library for everything from education, to model understanding, to art projects and much more.
It provides two APIs NumPy as for an immediate execution model and another as TensorFlow API for a deferred execution model mirroring. "We have also implemented versions of some of the most commonly used TensorFlow operations. With the release of Deeplearn.js, we will be providing tools to export weights from TensorFlow checkpoints, which will allow authors to import them into web pages for Deeplearn.js inference."
Demos for Deeplearn.js can be viewed on as of the project's homepage. The deeplearn.js provides us a wider scope to implement a great number of features and to have a whole new experience with more ease and flexibility. It has joined a number of projects to showcase the ability that it possess and provide a whole new range of tools.
More Information: GitHub