Machine learning involves teaching computers to recognize patterns in the same manner a human brain does. For example, it is effortless for us to differentiate between an apple and an orange or a cat and a dog. However, imagine if one has to teach a machine to do this. There are many approaches to Machine Learning. This video focuses on the supervised learning approach on the Google Cloud Platform.
Machine Learning on Google Cloud
Supervised learning involves giving your model labeled input during training. We can think of any supervised learning problem this way. You provide labeled inputs to your models then your models output a prediction. How your model works depends greatly on the tools you use for the job and the type of machine learning problem you are trying to solve.
Many revolutionary changes are happening in the IT landscape. There are plenty of tools and software that are Machine Learning. What is important to note is that, unlike earlier days, ML is no more only for the experts. Some tools and platforms make it easy for anyone to adapt them quickly. This video talks about the Google Cloud platform for Machine learning. It discusses the basics of ML, using the pre-trained ML model with a single API call. It then talks about building and training custom models with TensorFlow and Cloud ML Engine.