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Blogs for course projects in BBM406 — Introduction to Machine Learning, an undergraduate class at Hacettepe University — This year the theme is Machine Learning and Food..
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[Week7— Eat & Count]

In our Week-5 blog post, we have talked about training a ConvNet from scratch and shared our preliminary results. We have used AlexNet model and trained it on 10 classes from Food-101 dataset. The preliminary result that we get from this model is about 50% accuracy. But it is time consuming…


[Week5-YelpGuesser]

For Each Word, Find Corresponding Vector

Hello everyone,

This week we are talking about Wor2vec.Word2Vec allows us to calculate the distance between words in a vector. We can find words close to each other.Trained…


[Week5 — Eat & Count]

In our last blog, we talked about how to predict a given food photo’s kind and what was our convolutional neural network architecture. We implemented an AlexNet architecture and tried to train it from the beginning and we get some poor results.


[Week 3 — YelpGuesser]

Why We Need To Training and Test Set?

As we have already mentioned, our project we will use Yelp dataset. Firstly we have to say Yelp data is very huge.If we want to use our dataset useful for the project, we have to ask “When our predictions have an error, how…