Interview - Machine Learning that's ACTUALLY easy with Richard Campbell
Do you want to try machine learning, but don't want to invest too much time learning a new programming language or some other complicated API or complicated online tools?
Richard Campbell and I are geeking out about why you would want to look at machine learning, how to get started, and what should you know when building your prototype. 🧐
ML.NET Model Builder opens up the world of Machine Learning to all developers.
I had a blast doing the interview. I hope you'll enjoy watching it as much as I enjoyed making it! 😁
Updated demo (screenshots)
Here are updated screenshots for ML .NET v1.4 Model Builder.
Bonus
When using ML .NET Model Builder, it will try to determine if a column should be a hash table or text, which can have a significant impact on your use case. It decides based on the ration of unique and duplicate values and it might choose the wrong type because of that.
However, after generating the code, you can change from a hash table to text and vice versa.
- In file
ModelBuilder.cs
in methodBuildTrainingPipeline
change the.Append
for desired column.
From:
.Append(mlContext.Transforms.Categorical.OneHotHashEncoding(new[] { new InputOutputColumnPair("Description", "Description") }))
To:
.Append(mlContext.Transforms.Text.FeaturizeText(inputColumnName: "Description", outputColumnName: "Description"))
- Retrain model by running
ModelBuilder.CreateModel();
inProgram.cs
. Return right after training because the model hasn't been copied yet tobin
folder.
- Remove the code from step 2.
NOTE: If your project contains .
in it's name, chances are that the path to the model will be incorrect. (a bug since v1.3) Make sure that path MODEL_FILEPATH
in ModelBuilder.cs
is correct!