ML.NET Intro
ML.NET Introduction ML .Net(Machine Learning .NET) is an open-source machine learning library provided by Microsoft. It is also cross-platform & can run on Windows, Linux, macOS. It is mainly developed for DotNet developers. C# & F# can be used to develop ML.NET applications. Below are the steps in machine learning. 1. Algorithm: For working with ML, we need to select an algorithm e.g. clustering, regression, anomaly detection, etc. 2. Train: It is a process in which input data is analyzed by the algorithm. The output of the algorithm is the "Trained Model". This data is used to learn the pattern. With this trained model, predictions are made based on input. 3. Evaluate: This will be performed once the training step is completed. The model builder uses the trained model to make predictions for input data. 4. Code: Once the Evaluation phase is completed, the model builder outputs a file & code that can be used...