Machine Learning with ML.Net

www.Suhail.Cloud #SuhailCloud @SuhailCloud
Machine Learning with ML.NET
Suhail Jamaldeen

About Me
Suhail Jamaldeen
Consultant & Trainer – Office 365 | Azure
Microsoft MVP – Office Apps & Services
Speaker
Blogger – www.Suhail.Cloud
#SuhailCloud

Agenda
.Net Core
Machine Learning
ML.Net
Automated Machine Learning
ML.Net Model Builder
ML.Net CLI

.NET 5 = .NET Core vNext 3.0
Platform to build anything

Machine Learning
• Machine learning is a subset of Artificial Intelligence (AI)
• Provides systems the ability to automatically learn and improve
from experience without being explicitly programmed.
• Process
• Prepare Data
• Build Model (Acquire Knowledge)
• Use Model (Predict Decisions)
• Results are probabilistic

Machine Learning Workflow

Machine Learning Types
Supervised Learning
Classification
• Binary classification – Sentiment analysis
• Multi classification – Issue Classification
Regression
• Price prediction
Unsupervised Learning
Clustering
• Cluster customers into who purchase similar products

Artificial Intelligence vs. Machine Learning vs. Deep Learning

ML.Net
Machine Learning framework for building custom ML Models
Cross-platform and open-source available
Announced

Reuse .Net Skills
C# and F# for custom models
Proven at scale
Azure, Windows, Office
Used in PowerBI, Outlook, Visual Studio…
Extensible
Tenserflow, ONNX and Infer.Net
Custom LM made easy
Automated ML and Tools (Model builder and CLI)

Few samples from GitHub repository
https://github.com/dotnet/machinelearning-samples

ML.Net Machine Learning Samples
https://github.com/dotnet/machinelearning-
samples

Automated Machine Learning – AutoML (Preview state)
Automate the creation of the model
• You don't need to write the code by yourself to train a model
• You simply need to provide your datasets.
• The "best" model and the code for running it will be generated for
you.
Currently only support Binary-Classification, Multiclass
Classification and Regression.
In upcoming versions will be supporting additional ML Tasks such
as Recommendations, Anomaly Detection, Clustering, etc..

Available in three form factors
• ML.Net Model Builder
• ML.Net CLI
• ML.Net AutoML API (For ISVs)

ML.Net Model Builder (Preview)
• UI tooling in Visual Studio as Visual studio extension
• Uses Automated Machine Learning (AutoML) to easily allow to
build, train and ship custom machine learning models
• Developers with no ML expertise can use this tool easily
• Model Builder currently supports Regression, Binary-Classification
and Multi-Classification tasks.

• Currently support .tsv, .csv, .txt, and SQL as the data types
• If you have a .txt file, columns should be separated with ',' or ';' or
'/t‘
• The files must have a header row.

ML.Net Model Builder
www.aka.ms/dotnetmodelbuilder
https://github.com/dotnet/machinelearning-
samples/tree/master/modelbuilder

ML.Net CLI (Preview state)
The ML.NET CLI is a tool you can run on any command-prompt
• Windows – Poweshell and CMD
• Mac or Linux – Bash
Generates good quality ML.NET models based on training datasets
you provide.
It also generates sample C# code to run/score the model
Generates C# code that was used to create/train it so you can
research what algorithm and settings it is using.

Currently, the ML Tasks supported by the ML.NET CLI are:
• binary-classification
• multiclass-classification
• regression
Future: other machine learning tasks such
as recommendation, ranking, anomaly-detection, clustering
dotnet tool install -g mlnet
mlnet auto-train --task binary-classification --dataset "wikipedia-detox-250-line-
data.tsv" --label-column-name Sentiment --max-exploration-time 30

ML.Net CLI
https://docs.microsoft.com/en-
us/dotnet/machine-learning/automate-
training-with-cli

References
 https://dotnet.microsoft.com/
 https://github.com/dotnet/machinelearning-samples
 https://dotnet.microsoft.com/learn/ml-dotnet

Questions
&
Answers

Thank You
www.Suhail.Cloud
@SuhailCloud
#SuhailCloud

Machine Learning with ML.Net

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