Google Cloud AutoML: Powerful performance and efficient ML kit
What do you like best?
Google AutoML kit is one of the best platforms for developers of Machine Learning, as the main benefit is that it is from Google and ML is highly affected by Google. In that manner, Google's AutoML kit provides very sophisticated ML techniques and algorithms support. In addition to that, the performance and accuracy of AutoML algorithms are way better than other ML platforms. Create and train the model of any specific problems is very easy and fast. Google AutoML Algorithms and techniques can easily handle large and complex data processing and as is it on the cloud, I get extremely good GPU support that would rather cost me thousands of bucks. It really makes the difference in how I develop ML applications.
What do you dislike?
One thing I believe can be improved that Google can get know regarding my private data sets which sometimes can be a privacy issue for some users. So, Google may introduce some private data loading techniques on AutoMl platform. Other than that there are not any major issues in it.
Recommendations to others considering the product:
Google Could AutoML is a very cost-effective solution in terms of hardware resources. Also, with that, you will get security as well as reliable performance for any kind of complex data you want to process. Definitely anyone who is working in ML should go with it once.
What problems are you solving with the product? What benefits have you realized?
I use Google Could AutoML for various purposes such as data preprocessing, dataset manipulation and mainly for model training. We have monthly subsciption based plan for Google AutoML platform at our company and as a machine learning developer, I am utilizing it for developing a different pilot application for demo purpose as well as main projects of ML in it.