OpenCV and Streamlit: create a photo editing app

Manipulating images is a task that is very useful in several application fields. OpenCV, a Python library, easily allows us to modify images according to our needs. In this tutorial we discover how to build a simple web app using Streamlit to apply some effects to our photos.

Streamlit: Build a Web App in minutes

Developing web apps requires a lot of skills not only related to data management and manipulation, but especially data visualization. Using visualization software such as Kibana and Tableau can, in some cases, be the salvation to reduce development time. With Streamlit, a Python framewrok, you can very quickly develop a web app or interactive dashboard without any frontend programming skills. This tutorial will illustrate how you can do it in a few minutes.

GPT-2: automatic text generation with Python

Generating textual content is a challenging job that requires time and resources. With artificial intelligence, it is now possible to generate content simply from a few words. The technologies developed by OpenAI, including GPT-2, have opened new frontiers of application related to Natural Language Generation. Let’s find out how to automatically generate short texts using a few lines of Python code.

Pillow: optimize images with Python

Optimizing images is key to making websites faster and improving SEO. With the advent of WebP format, it is possible to provide quality images but much “lighter”. In this article we discover how to transform jpg and/or png images into the webp format using a few lines of code written in Python and the Pillow library.

Node.js vs Python: comparing the two technologies for the backend

Choosing a programming language for the backend development of an application is a crucial step. There are several languages that meet the needs of various projects. In this article, we analyze Node.js and Python, the two most widely used languages, to discover their features and provide a guide for an informed choice.

Jupyter Notebook: user’s guide

The development of data analytics pipelines by Data Scientists requires several skills. Having an easy, intuitive, and interactive development environment is critical. Jupyter Notebook is an open source web application that allows you to create and share interactive textual documents, containing objects such as equations, graphs and executable source code in different languages. Let’s discover its main features.

Chatterbot: create a chatbot in python

Chatbots are a technology that allows you to automate interaction with users. Leveraging the latest artificial intelligence technologies, conversations turn out to be more and more real. Examples of chatbots evolution are virtual assistants like Alexa, Cortana and Siri. Let’s find out how you can develop a simple chatbot in Python using the Chatterbot library.

Pandas and Bokeh: create interactive graphics

Analyzing data also requires graphing the data or the results from the analysis performed. Many libraries in Python provide useful tools for visualization, but the plots produced are static. The Pandas Bokeh library is a great alternative for creating interactive plots and including them in web projects. Let’s find out how to use it and the results we can achieve through some examples.

PandasGUI: Graphical user interface for analyzing data with Pandas

Pandas is the most used library by data scientists to analyze data. But if you are not an expert programmer or simply want to explore your data in a simple and intuitive way you can use PandasGUI. This is a library that allows you to view and interact with Pandas dataframes with a simple mouse click.