Detecting Spam Messages Is NOT That Hard

Hello everyone again. We will detect spam messages today. So how do we do that? We will look at the old messages and learn and remove the unnecessary messages from our message box. I want this article to be short and to the point. I would like to have an article that you can read immediately and add something to yourself. In just a few minutes, you can detect spam messages with just a few lines of code.

As always, we are adding the necessary libraries. Today I will show you how you…

In data science, visualization is very important. It allows us to see the data more clearly and makes it fun to examine the data. If you are working on a project and need to turn your work into a presentation and explain it, using visualization can be a lifesaver. Because most of the time, the codes you write will not be equally descriptive and understandable for everyone. This is where visualization comes into play. I will show you different ways of visualization with a supermarket data set.

First thing first, we have to read the data and apply “EDA” so…

Hello hello, here we are again. In my article last week, I mentioned EDA (Exploratory the Data). We all know how important it is to understand data. So what if I told you there was an easier way to do this? While we were taking artificial intelligence lessons, when we got to the middle of the training, we knew EDA as well as our name. And our teacher told us about the Pandas Profiling Report (PPR). I remember how surprised we were with the ease and features of PPR in every detail. So let’s get started.

Of course, our first…

Hello there, here we are again. Today I will tell you the first step that we data scientists take in data analysis. The great “EDA” :)
EDA stands for “Exploratory the Data”. So what does this EDA do? Why do we use it? How do we use it? etc. Don’t worry, you will get the answers to these questions and more now. So If you’re ready, let’s get started.

In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. …

Hello everyone again. In this article, I will talk about a machine learning library that provides me great convenience.

In machine learning, analyzing data and preparing the data before giving it to the model is of great importance. When I say preparing data, I’m talking about filling empty data, getting rid of outliers, doing future engineering, etc. As data grows and becomes more complex, you will spend more time implementing these processes. But with Pycaret it’s quite the opposite.
Pycaret is a low-code machine learning library. Whether it’s imputing missing values, transforming categorical data, feature engineering, or even hyperparameter tuning of…

Hello everyone, this is my first post on Medium and in this article, I will talk about how I became a Data Scientist just in a month and what I am doing with it right now.

First of all, I must say that my biggest dream was to study and learn Data Science, Machine Learning, and Artificial Intelligence and learn as much as I could in this field. So, how did I achieve this?

If we go to the beginning of this adventure, in November, you will see how unexpectedly everything has developed. At the beginning of this year, I…

Şeyda Arı

Data Scientist / Electric and Electronic Engineering Ege University / /

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