[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.

[Week 4 — Classification or Regression]

What do we need when predicting scores of the reviews?
Which one is better for our…

Week 3 — Estimating Preferences By Region Using Yelp Data

[Week 3 — Features and Classification]

The week we passed we started to collect our own Turkish dataset. In this week, we began to investigate how we will use these comments we collected and the classification process. We have the basic two steps we need to do.

Week 1 — Estimating Preferences By Region Using Yelp Data

[Week2 — Eat & Count]

In this week we researched convolutional neural networks which we will be use it in our food recognition part of the project. We examined the differences between convolutional neural networks and regular neural networks. And we briefly explained the layers in ConvNets.

[Week 1 — Hello Restaurant]

This is our first article. Let us to talk about that what will we do/work in this project.

The sentiment analysis is one of work area in machine learning and there are many related researches associated text/documents classification, spam filtering. Our…

[Week 2— Collection Reviews]

We collect our data. But there is a problem with collected reviews, misspelling words. Misspellings need to be corrected to ensure the safety of the comments we collect. We need to do a simple natural language processing for it. We found a ready-made Python code that converts…

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…