A final test is required to make

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Train the algorithm You've got your data ready and your model selected. Now it's time to get to know them, right? The long process of feeding the algorithm with the chosen sources is called training. As you do this, you'll need to fine-tune the parameters to make it learn the underlying patterns.


You'll also need to evaluate its performance lithuania mobile database using cross-validation techniques. Roughly speaking , you first need to dump all the filtered sources into the model and ask it to perform simple tasks. However good the data may be, the system needs to accumulate enough experience to provide satisfactory results.


Through trial and error, it will improve its outputs . Make a final evaluation You've probably guessed it already: anyone who programs artificial intelligence must be a born perfectionist. sure everything works as expected. Is the system's performance not up to your expectations? Then start tweaking its parameters until it does! In this final evaluation, we will feed a new validation data package to the algorithm to check that it identifies replicable patterns.