Course Projects for Introduction to Machine Learning, an undergraduate class at Hacettepe University — This semester the theme is Machine Learning and Food..

Jan 19, 2017

[week6-YelpGuesser]

Experimental Results

Hi,

Finally we finished our project. At the end of the project we learned a lot of information about machine learning and text mining issues.We want share with you our experimental results and some parts from our final…

Machine Likes It in bbm406f16

Jan 18, 2017

Final Week— Estimating Preferences By Region Using Yelp Data

Just like everything else, our project has come to an end. We learnt so much on the way and tried to come up with new thing and discover machine learning world a bit more.

Eat & Count in bbm406f16

Jan 14, 2017

[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…

YelpGuesser in bbm406f16

Jan 6, 2017

[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…

Eat & Count in bbm406f16

Jan 4, 2017

[Week6 — Eat & Count]

In our project, our goal is to understand a given photos’ class and calculate the calorie of foods eaten in a period. In previous blogs, we talked about image classification, how to understand the kind of a given test food photo. In this blog, we will be talking about the second part of…

Sentiment Analyzer in bbm406f16

Jan 4, 2017

[Week 5 — NLP Zemberek]

Zemberek is an open source Turkish language linguistic processing library. The fully Java-developed library has features such as spell checking, suggestions for incorrect words, hyphenation, deasciifier, and erroneous code clearing.

Eat & Count in bbm406f16

Jan 1, 2017

[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.

Machine Likes It in bbm406f16

Dec 30, 2016

Week 5 — Estimating Preferences By Region Using Yelp Data

In this week we did more experiments. And we have same results, yay!

First of all, choosing a topic count and other parameters are such a hard decision. Because all of them differs according to the review…

YelpGuesser in bbm406f16

Dec 29, 2016

[Week4-YelpGuesser]

Choose the Most Suitable Algorithm and Get the best Predictions!

Hi Everyone

Today we are going to talk about the SVR algorithms. Immediately created our datasets.We designed what dataset to use in…

OriginsOfFood in bbm406f16

Dec 28, 2016

[Week-3 Origin of Food]

Some reviews about our architecture and our main goal.

After we published our progress report, we got some reviews about our architecure and main goal’s of the system from our advisor Asst.Prof.Dr Aykut Erdem. According to that review, we realize that we have…

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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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