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Introduction

In this tutorial, we will fine-tune a transformer model for the Sensitivity classification problem. If we look at the basics of sentiment classification, we will realize that multi-class classification is actually a special case in NLP. In this case, there are classes that represent the emotion represented by the text, and we try to guess them. The number of classes usually ranges from 3 to 5, but of course, it is likely to vary, generally, classes are found in positive, negative, and neutral.

Sentiment Classification is often one of the most common business problems when trying to determine the sentiment…


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In this tutorial, we will be fine-tuning a transformer model for the Multi-Class text classification problem. This is one of the most common business problems where a given piece of text/sentence/document needs to be classified into one or more categories out of the given list. As we will discuss in this tutorial, it can be used in many areas such as news types or article types.

Don’t explain to me, show the code

You can access the GitHub repo here.

We use the dataset named Interpress Turkish News Category Dataset (270K) prepared by Interpress and included in HuggingFace. The data set consists of 2 parts, split as…


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Update: This article is part of a series in which I explored the time series. Check out the full series: Part 1, Part 2, Part 3

Here are the average monthly temperatures from Florida since 1743, which I discussed in the previous article. In this article, I will first demonstrate basic level operations using LSTM with this dataset.

Don’t explain to me, show the code

You can access the GitHub repo here.

Long short-term memory (LSTM) is an artificial repetitive neural network (RNN) architecture used in the field of deep learning. Although it is not different from RNN in terms of working logic, it allows much longer…


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Update: This article is part of a series in which I explored the time series. Check out the full series: Part 1, Part 2, Part 3.

I have monthly average temperatures from Florida since 1743, which I discussed in the previous article. In this article, firstly I will explain basically some models and their definition and show you basic operations in time series using models such as ARIMA, SARIMA with this dataset.

Don’t explain to me, show the code

You can access the GitHub repo here.

Estimation is made by a linear combination of observations from previous time steps.
It is suitable for univariate time series without trend…


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If I explain the time series in the simplest way; Time series are used for predictions based on the current series, and they are also used in hypothesis tests.

Update: This article is part of a series in which I explored the time series. Check out the full series: Part 1, Part 2, Part 3.

Don’t explain to me, show the code

You can access the GitHub repo here.


Photo by Markus Winkler on Unsplash

Don’t explain to me, show the code

You can access the GitHub repo here.

By definition, Dynamic pricing is a pricing strategy in which prices change in response to real-time supply and demand. However, when we think about it more deeply, it is the pricing form of the product or service made by taking into account the different parameters in the market. …


If you are someone who thinks “how many stars should I give” when you buy a product from Amazon like me, this medium article is for you.

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In this project, I chose the Electronics dataset among the datasets containing the comments belonging to Amazon. I made an application by choosing the best model among the models I trained and published it on Heroku.

Nowadays, the product and criticism are happening beyond the private pages and also take place in the social media space.

When I review reviews for electronic products on Amazon, most of the product reviewers have scored between…


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No matter how much we are not aware of the recommendation systems in our daily life, they are services that are almost instant and can direct us when necessary. However, recommendation systems are basically created to predict what users might like, what they need and present them to users when there are many options available.

When there are too many options, they quickly present them to the user by running in the background and indexing them, rather than processing them and keeping the user waiting.

Although creating a simple recommendation system is thought to be quite simple, the difficult part…


https://carlolepelaars.nl/2018/10/15/100daysofmlcode-summary/

When most people hear “Machine Learning”, they picture a robot: a deadly Terminator or a dangerous computer, which wants to destroy humanity just like in the Matrix movie.

But welcome to reality, Machine Learning is not just a futuristic fantasy; it’s already here. In fact, it has been around for decades in some specialized applications, such as movie recommendation systems in online Movie/Series Platforms.

But in my opinion, the first ML app that really became indispensable, the spam filter. It’s not exactly Skynet or Agent (from Matrix), but it does technically qualify as a Machine Learning. It has…


In this project, I will try to handle Data Analysis in a different way and if I were to open a restaurant for a good Turkish meal in Milan, where I live, I will think about where I should open it.

First of all, since I had no data, I researched where I could learn the Milan regions and I could access Milan information on Wikipedia. First of all, I made this information so that I can retrieve the information through BeautifulSoup.

Ogulcan Ertunc

I’m a Master Student🎓pursuing Data Analytics. I’m a Data Enthusiast 💻 😃 passionate about learning and working with new tech. https://github.com/ogulcanertunc

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