Google’s Cloud Machine Learning has gone into its public beta. An announcement to the effect was made today and is another major step along what Google likes to refer as the Google Cloud Era. The program is meant to let businesses to train quality machine learning models at a faster rate and otherwise use all the advancements made in Machine learning to their advantage.
Before we go any further, lets take a quick moment to look into what the platform actually is and what it does. The Cloud Machine Learning, is service provided by the software giant that enables businesses to build machine learning models able to work on any type of data, of any size. The service uses the same TensorFlow framework that is behind several of Google’s own products, including Google Photos and Google Cloud Speech.
The service was announced earlier this year and is now available in public beta. One of the biggest advantages of deploying this service is that you are basically deploying Google’s infrastructure to handle your data. And as we already know, Google’s infrastructure is as scalable as it gets. So, while using its Cloud Machine Learning tools, you can train models on terabytes of data within hours. Doing the same on many similar services out there could take you anywhere between a few days.
Google has also announced a brand new feature called HyperTune, that is expected to make the job of building models a lot easier for data scientists.
We’re also introducing a new feature, HyperTune, that automatically improves predictive accuracy. It allows data scientists to build better performing models faster by automatically tuning hyperparameters, instead of manually discovering values that work for their model.
Google also talked about how one of its customers — namely, Airbus Defense and Space — was able to successfully use Google Cloud Machine Learning to automate the process of detecting and correcting satellite images that contain imperfections such as the presence of cloud formations.
It should be mentioned that the process of cloud-correction (in a manner of speaking) is both time consuming, insanely complicated and pretty hard to scale. By using Google’s Machine learning systems, Airbus defense and space was able to significantly improve the precision and reliability of the information it provides to its customers.
Speaking about the testing experience, Mathias Ortner, Data Analysis and Image Processing Lead at Airbus, said:
In our tests, Google Cloud Machine Learning enabled us to improve the accuracy and speed at which we analyze the images captured from our satellites. It solved a problem that has existed for decades.
The tech major has also launched a couple of brand new solutions that are aimed towards helping businesses and corporations identify how Machine learning can be used to solve individual problems. While the first, Machine Learning Advanced Solutions Labs, lets businesses directly get in touch with Google Machine Learning engineers to help them solve their complex problems, the second Cloud Start program is meant to offer educational workshops for businesses. The workshops will let them learn more about public clouds and enable them to identify opportunities using machine learning.
Finally, the company also announced a certification program for bringing machine learning to as many people and businesses as possible. The program is run by Google itself and the course material will be designed and aught by Googlers. So you can expect to be taught by some of the best in the industry.
We recognize that machine learning has traditionally required specialized training and expertise. By opening these programs, more users can learn to create new machine learning applications.
Meanwhile, the company is probably hoping to get more people abroad the machine learning train. Machine learning is truly incredible and is one of the most fantastic advancements made by today’s technology. However, there is a significant lack of people able to work, simply because the technology is too new for there to be as many training resources — or awareness for that matter — as there are for say, Android.
Google is hoping to bridge the gap and with the kind of expertise it has the field, it is certainly in a position to do so. These announcements and particularly the certification program, are a significant step in the right direction.