Learn Tensorflow: Smarter Car Learning, For Everyone
Just a distich of years ago, y'all couldn’t speak to the Google app through the dissonance of a metropolis sidewalk, or read a sign inward Russian using Google Translate, or right away honour pictures of your Labradoodle inward Google Photos. Our apps but weren’t smart enough. But inward a brusque sum of fourth dimension they've gotten much, much smarter. Now, thank y'all to machine learning, y'all tin terminate create all those things pretty easily, together with a lot more. But fifty-fifty amongst all the progress we've made amongst machine learning, it could withal locomote much better.
So we’ve built an exclusively novel machine learning system, which nosotros telephone phone “Smart Reply inward Inbox, to search inward Google Photos. It allows us to laid together with educate neural nets upwards to 5 times faster than our first-generation system, then nosotros tin terminate purpose it to improve our products much to a greater extent than quickly.
We've seen firsthand what TensorFlow tin terminate do, together with nosotros mean value it could brand an fifty-fifty bigger comport on exterior Google. So today we’re likewise open-sourcing TensorFlow. We promise this volition allow the machine learning community—everyone from academic researchers, to engineers, to hobbyists—exchange ideas much to a greater extent than quickly, through working code rather than but question papers. And that, inward turn, volition accelerate question on machine learning, inward the cease making applied scientific discipline locomote amend for everyone. Bonus: TensorFlow is for to a greater extent than than but machine learning. It may hold out useful wherever researchers are trying to brand feel of rattling complex data—everything from poly peptide folding to crunching astronomy data.
Machine learning is withal inward its infancy—computers today withal can’t create what a 4-year-old tin terminate create effortlessly, similar knowing the refer of a dinosaur later on seeing only a distich examples, or agreement that “I saw the Grand Canyon flight to Chicago” doesn’t hateful the canyon is hurtling over the city. We accept a lot of locomote ahead of us. But amongst TensorFlow we’ve got a practiced start, together with nosotros tin terminate all hold out inward it together.
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We've seen firsthand what TensorFlow tin terminate do, together with nosotros mean value it could brand an fifty-fifty bigger comport on exterior Google. So today we’re likewise open-sourcing TensorFlow. We promise this volition allow the machine learning community—everyone from academic researchers, to engineers, to hobbyists—exchange ideas much to a greater extent than quickly, through working code rather than but question papers. And that, inward turn, volition accelerate question on machine learning, inward the cease making applied scientific discipline locomote amend for everyone. Bonus: TensorFlow is for to a greater extent than than but machine learning. It may hold out useful wherever researchers are trying to brand feel of rattling complex data—everything from poly peptide folding to crunching astronomy data.
Machine learning is withal inward its infancy—computers today withal can’t create what a 4-year-old tin terminate create effortlessly, similar knowing the refer of a dinosaur later on seeing only a distich examples, or agreement that “I saw the Grand Canyon flight to Chicago” doesn’t hateful the canyon is hurtling over the city. We accept a lot of locomote ahead of us. But amongst TensorFlow we’ve got a practiced start, together with nosotros tin terminate all hold out inward it together.
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