Google Cloud ML Engine can be used for rescue. It is a host platform where developers of machine learning apps and data scientists build and run machine learning models of optimum quality. If you’re training your classifier on a small dataset, maybe your Desktop or laptop will work really well. If you have training data in the millions or billions, though? Or, is the algorithm fairly complex and takes a long time to execute properly?
Google Cloud ML Engine
With the Cloud ML Engine, you can use Google’s distributed machine network to train your ML model in the cloud. Google can run your training algorithm on several computers to speed up the process, instead of only using your laptop to train your model. You can also customize the types of CPUs / GPUs on which those computers are operating. There are some algorithms that run much faster if you use GPUs rather than CPUs.
Another advantage we have noticed from Cloud ML Engine training is that you don’t have to think about storing the training data. If you have a million emails to train your spam filter how do you get them to train your software on your laptop? For this purpose, training data is stored online in Google Cloud Storage “Bucket” when you train your model using the Cloud ML.
- Provides preparation, development, deep learning and predictive modeling for the machine learning platform.
- The two divisions viz. Prediction and preparation can be implemented individually or in combination.
- Businesses use this program extensively, i.e., detecting clouds in a satellite image, responding more quickly to customer emails.
- This can be used extensively for training a complex model.