A presentation about Machine learning using ML.NET

1. Machine Learning With
ML.Net

2. Introduction
• ML.Net is Microsoft Machine Learning(ML) Library for creating ML
models
• It has been used in many Microsoft products such as Windows,Bing
Search Engine, Azure Machine Learning e.t.c.
• With this ML library you can create ML models for many things such
as:
1. Sentiment Analysis(Our interest)
2. Product Recommendations
3. Price Prediction
4. Image Classification
5. And many more...

3. Steps in creating an ML model in ML.Net
1. Create a Console project
2. Have a DataSet
3. Create a class based on DataSet for data schema
Inside Main method of Console project
1. Create instance of MLContext
2. Load Data from dataset
3. Split data into train data and test data
4. Build and train the model
5. Evaluate the accurancy model
6. Save the model for later use

4. Our DataSet

5. DataSet Schema

6. Create MLContext Instance
• Starting point for ML.NET
• Have properties for:
1. Loading Data from DataSet
2. Preparing and Transforming Data
3. Specifying ML algorithims
4. Loading and saving trained model
5. Many more...

7. Load Data from DataSet

8. Build and Train Model(+pipeline)

9. Use Model to Make Predictions

10. Evaluating Accurancy of our Model

11. Saving our Machine Learning Model