Merge pull request #94 from biolab/new-image-tutorial

Blog: New Text Mining Tutorial

public/blog/2024-04-new-image-tutorial/index.md

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+---
+author: "Erika Funa"
+date: "2024-04-15"
+draft: false
+title: So Sweet and So Fresh … New Text Mining Tutorial is Out
+url: "new-image-tutorial"
+thumbImage: "2024-04-12-word-classification.png"
+frontPageImage: "2024-04-12-word-classification.png"
+blog: ["image", "tutorials"]
+shortExcerpt: "A step-by-step guide on how to
+build a classifier to predict food types. Getting the know the widgets
+Test and Score, Logistic Regression, Confusion Matrix, Predictions."
+longExcerpt: "New Text Mining Tutorial: a step-by-step guide on how to
+build a classifier to predict food types. Evaluating model accuracy, looking at
+misclassifications, and extending predictions to new foods. Getting the know
+the widgets Test and Score, Logistic Regression, Confusion Matrix, and Predictions."
+---
+
+In our Text Mining Series on Youtube, you can find [a new tutorial video](https://www.youtube.com/watch?v=kLoe8oV9mxw&list=PLmNPvQr9Tf-bxmjlFRg0AGjMzzd1y8_kB&index=10), this time inspired by food.
+
+In the video, we look at word classification and show you step-by-step how to build a classifier to predict food types. We then evaluate model accuracy, look at misclassifications, and extend predictions to new foods. You will get to know the following Orange widgets: Test and Score, Logistic Regression, Confusion Matrix, and Predictions. 
+
+You can [download the data file](https://file.biolab.si/files/words-food.xlsx), or load this data using the Dataset widget, where the Target Variable is already set to Category. 
+
+The Text Mining series takes you into the world of machine learning, visual analytics, and interactive analysis of text documents with Orange. Its development has been supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenian Ministry of Digital Transformation, the European Union (including xAIM and ARISA), and Google.org/Tides foundation.
+
+If you want to dive further into classification-related content, you can check out our [Intro to Data Science series](https://www.youtube.com/watch?v=7I3d0HdUjsk&list=PLmNPvQr9Tf-b_SuBdoRsuNhTmaHJ0eKab&index=30) and if you like our content, you are very welcome to join our community by subscribing to [our Youtube channel](https://www.youtube.com/orangedatamining) or following us on [LinkedIn](https://si.linkedin.com/company/orange-data-mining) or [Facebook](https://www.facebook.com/orangedatamining/).
+
+Looking forward to hearing how you liked our spring menu!