Training a larger model In the sections before we use images of size 150×150 because the model can be trained faster (here:4 times faster). This is a good way when experimenting with parameters. Now we want to train on bigger images – let’s use images of size 299×299. Therefor we reuse the previous code forContinue reading “ML Zoomcamp 2023 – Deep Learning – Part 13”
Tag Archives: Training
ML Zoomcamp 2023 – Deep Learning – Part 12
Data Augmentation In the last section we talked about how to stabilize the network performance while we use dropout. This way we focus on overall shape instead of focussing on details like logos. It works because in each epoch another part of the network (not of the image) is hided/frozen. So small details like logosContinue reading “ML Zoomcamp 2023 – Deep Learning – Part 12”
ML Zoomcamp 2023 – Deep Learning – Part 9
Checkpointing Checkpointing is a way of saving our model after each iteration or when certain conditions are met, f.e. when the model achieves the best performance so far. This is a nice way because when the model starts to oscillate, the model after 10 iterations is not necessarily the best one. Saving the best modelContinue reading “ML Zoomcamp 2023 – Deep Learning – Part 9”
ML Zoomcamp 2023 – Deep Learning – Part 7
This is the second part of Transfer Learning section. While in the last article we looked at reading image data this article covers the training part. Transfer Learning – Part 2/2 Train Xception on smaller images (150×150) (Better to run it with a GPU) So far for reading the data, now let’s train a model.Continue reading “ML Zoomcamp 2023 – Deep Learning – Part 7”
ML Zoomcamp 2023 – Introduction to Machine Learning – Part 2
Overview: The second part is about the distinction between Machine Learning (ML) and rule-based systems. The example of a spam filter is used to explain how the implementation would look like without ML. Rule-based systems What you need to do is to define some rules to distinguish between ham and spam. So you start definingContinue reading “ML Zoomcamp 2023 – Introduction to Machine Learning – Part 2”
ML Zoomcamp 2023 – Introduction to Machine Learning – Part 1
Overview: This is a summary of what I’ve learned from the great ML course (http://mlzoomcamp.com) by Alexey Grigorev. All images from this post are from the course material. Images in other posts can also be copies of that material. The introduction starts with an explanation about what ML really is. You can imagine a taskContinue reading “ML Zoomcamp 2023 – Introduction to Machine Learning – Part 1”
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