In this article, which is the third part of the “Python Under the Hood” series, I will be talking about the two important components in the Python Ecosystem, namely Pip and Conda. If you didn’t read the first part and the second part of the series, you can refer to them here and here.

So, what are Pip and Conda ? And what are the diffrences ?

Pip is the way-to-go Python package manager to install Python packages that are hosted on the Python Package Index (PyPI).

Conda on the other hand is a general-purpose package manager…


In this article, which is the second part of the “Python Under the Hood” series, I will be talking about the interpretation phase of the Python language, describing key features of the Python byte code and CPython. If you didn’t read the first part, you can refer to it here.

Let’s start by doing a quick recap; As we saw in the first part, Python language is actually a compiled and interpreted language. …


In this article, which is planned to be a part of a series of articles, I will be talking about Python’s inner workings, explaining some concepts about the Python compiler, interpreter, and the CPython implementation.

First, is Python a compiled or interpreted language?

The answer is both, as you will see. Your Python code is actually compiled into bytecodes and then executed in the Python virtual machine by the interpreter!


Hello everyone, today I will continue with the final part of the series of the development of the machine learning project DASM (Damage assessment system for imagery data).

After the hard work that we did on labeling the data, we have now a total of 3627 images. As follow:


credit: Paradox Interactive‬`s “Skylines — Natural Disasters” game poster

So hello everyone, and welcome back!

Today I will continue talking about our Damage Assesment System For Imagery Data (DASM) project, and mainly about how we are building the dataset.

Since the idea of our project, is unique, we could not find a suitable dataset to use, in order to train our Machine learning models.

So we decided to build our dataset by ourselves.


So hello everyone. Today I'm gonna talk about our Damage Assessment System For Imagery Data project, shortly DASM. This project is the course project for BBM406 Introduction To Machine Learning Course.

I will start by Introducing our team: Ezgi Güngör, Malek Baba and nisahopcu. We are three undergraduate students in the Computer Engineering department at Hacettepe University.

Problem Description

DASM project aims to better analyze the image data that flows in the different social media platforms, especially during Natural disasters. Analyzing this data will help in developing better and more focused emergency response plans and facilitating damage assessment surveys.

Basically, we are…


Malek Baba

Software Engineer And Data Science Enthusiast.

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