This content originally appeared on DEV Community and was authored by Duc Nguyen Thanh
Hello, I’m Duc Nguyen (Duke)
Today I will introduce ML.NET to the .NET community
So, what’s the ML.NET?
- ML.NET is a cross-platform machine learning framework developed by Microsoft
- Open source
- Used in situations where it’s necessary to incorporate machine learning into C# or F# applications in order to avoid switching to other programming languages, such as Python (.NET ecosystem).
- Able can be expanded to function with additional machine learning libraries, like TensorFlow, assisting in utilizing current models and lowering obstacles to ML.NET adoption.
- Can be deployed in various environments, from desktop apps to web services
Alright, first you can get the source code from my repository here
Then, you can see:
- HaNoi-VN_housing_dataset.csv: sample data file used for training
- lib/HousePriceForecast.consumption.cs: Defines the “Predict” method, which takes input data and returns predictions using the trained model
- lib/HousePriceForecast.evaluate.cs: Defines the method for calculating PFI (Permutation Feature Importance) through the “CalculatePFI()” method — determines the level of influence from input data
- lib/HousePriceForecast.mlnet: Binary file containing the trained ML.NET model and related metadata and if there’s a similar project, this model can be reused without retraining
- lib/HousePriceForecast.training.cs: Used to train the ML.NET model and defines data processing steps and algorithm selection
Now, on to the fun part, practice!
You can also refer to the animation image here
This content originally appeared on DEV Community and was authored by Duc Nguyen Thanh
Duc Nguyen Thanh | Sciencx (2024-09-22T01:00:00+00:00) [ML.NET] Predicting the Future with ML.NET with examples. Retrieved from https://www.scien.cx/2024/09/22/ml-net-predicting-the-future-with-ml-net-with-examples/
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