Leony 12219018
One of these days, I believe that cloud computing, especially on Google Cloud, is very practical. Thus, I've been exploring google cloud on an annual challenge by Google Devs ID. I'd explored Google Cloud on various kind of matters, starting from BigQuery to security issues like proxy managing, but the products that I favor the most are BigQuery, TensorFlow, and website hosting.
The majority of BQ consists of cloud data processing (which is available through GCloud database). It's really useful to process a large amount of data available on cloud so that you don't need to use all of your PC processor to process the whole data. Commonly, BQ uses SQL for data processing language, and you can download the processed data with .xlsx or .csv file.
The TensorFlow that I will be explaining will be specified on Google Cloud (as I've just learned regarding TensorFlow from GCloud). Mainly for ML model training, I am specifically interested in its usage for data visualization after the data is trained through the model. TensorFlow also supports multiple language, so I find it to be convenient. I've just explored TensorFlow (specifically Keras API) for a short time and would love to learn more especially about image learning (other APIs regarding visual manipulations)
Website hosting (though expensive, but I have the chance to enjoy the service freely through the challenge) has its special perk when it comes to Google Cloud. All you need to do is upload your website essentials from github to Google Cloud Platform, and you can manage your website through hosting freely (and the fact that you can manage its firewall access is cool). Overall, website hosting made easier!
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