Hands-On Deep Learning for IoT

General ML rule of thumb

The general ML rule of thumb is that the more data there is, the better the predictive model. However, having more features often creates a mess, to the extent that the performance degrades drastically, especially if the dataset is multidimensional. The entire learning process requires input datasets that can be split into three types (or are already provided as such):

• A training set is the knowledge base coming from historical or live data that is used to fit the parameters of the ML algorithm. During the training phase, the ML model utilizes the training set to find optimal weights of the network and reach the objective function by minimizing the training error. Here, the backpropagation rule, or an optimization ...