Machine Learning component part1
The design choices to be made while building the machine learning server were: 1. Train the model in real time 2. Train the model in batches beforehand and predict in real time 3. Keep samples of data for training. Train and predict in real time The factors that help decide which approach to use are: 1. Volume of training data and How much time does it take to train the model? If the training takes too long, there is no point in real time model building. We would need to build the model apriori. Load the model in real time and use real time streams as test flows. The machine learning algorithm chosen in this project takes less time to train(~2-5 seconds) , hence we can afford to learn, train and predict in real time. 2. Criticality of accuracy, how much error is reasonable? If the accuracy obtained is greater than 85%, its reasonable to go ahead and predict using the model. If not we will need ...