Massaging Data Using Pandas

When we talk about managing data, it is quite inevitable to see data presented in tables. With column header, and sometimes with names for rows, it makes understanding data easier. In fact, it often happens that we see data of different types staying together. For example, we have quantity as numbers and name as strings in a table of ingredients for a recipe. In Python, we have the pandas library to help us handle tabular data. After finishing this tutorial, […]

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Web Crawling in Python

In the old days, it was a tedious job to collect data, and it was sometimes very expensive. Machine learning projects cannot live without data. Luckily, we have a lot of data on the web at our disposal nowadays. We can copy data from the web to create our dataset. We can manually download files and save them to the disk. But we can do it more efficiently by automating the data harvesting. There are several tools in Python that […]

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Managing Data for Machine Learning Projects

Big data, labeled data, noisy data. Machine learning projects all need to look at data. Data is a critical aspect of machine learning projects, and how we handle that data is an important consideration for our project. When the amount of data grows, and there is a need to manage them, allow them to serve multiple projects, or simply have a better way to retrieve data, it is natural to consider using a database system. It can be a relational […]

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A First Course on Deploying Python Projects

After all the hard work developing a project in Python, we want to share our project with other people. It can be your friends or your colleagues. Maybe they are not interested in your code, but they want to run it and make some real use of it. For example, you create a regression model that can predict a value based on input features. Your friend wants to provide their own feature and see what value your model predicts. But […]

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Web Frameworks for Your Python Projects

When we finish a Python project and roll it out for other people to use, the easiest way is to present our project as a command-line program. If you want to make it friendlier, you may want to develop a GUI for your program so people can interact with it with mouse clicks while it runs. Developing a GUI can be difficult as the model of human-computer interaction is complex. Therefore, a compromise is to create a web interface for […]

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Using OpenPose with Stable Diffusion

We have just learned about ControlNet. Now, let’s explore the most effective way to control your character based on human pose. OpenPose is a great tool that can detect body keypoint locations in images and video. By integrating OpenPose with Stable Diffusion, we can guide the AI in generating images that match specific poses. In this post, you will learn about ControlNet’s OpenPose and how to use it to generate similar pose characters. Specifically, we will cover: What is Openpose, […]

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More Prompting Techniques for Stable Diffusion

The image diffusion model, in its simplest form, generates an image from the prompt. The prompt can be a text prompt or an image as long as a suitable encoder is available to convert it into a tensor that the model can use as a condition to guide the generation process. Text prompts are probably the easiest way to provide conditioning. It is easy to provide, but you may not find it easy enough to generate a picture that matches […]

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Highlights from Machine Translation and Multilinguality in April 2024

Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation Folks from the University of the Basque Country prepared an English-Spanish dataset for natural langauge inference (i.e., deciding if sentences follow from each other, are in contradiction, or have nothing to do with each other) with metaphorical expressions. Unlike the standard version of this task (XNLI), which does not use figurative language, there is a large gap between in-language training and language transfer. (Transfer means that we finetune a multilingual […]

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3 Ways of Image Addition in Python with NumPy, OpenCV and Pillow Libraries

Introduction Addition of images might sound weird but people forget that an image is essentially a collection of numeric pixels. So we can do pixel-wise addition of the two images resulting in a new image. In this article, we will see multiple ways we can perform the addition of images in Python by using NumPy, OpenCV, and PIL libraries. Addition of Images When we add two images it does pixel-wise addition where each pixel in one image is added to […]

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Quiz: The Python calendar Module

Interactive Quiz ⋅ 6 QuestionsBy Bartosz Zaczyński In this quiz, you’ll test your understanding of creating calendars in Python using the calendar module. By working through this quiz, you’ll revisit the fundamental functions and methods provided by the calendar module. The quiz contains 6 questions and there is no time limit. You’ll get 1 point for each correct answer. At the end of the quiz, you’ll receive a total score. The maximum score is 100%. Good luck! « Browse All […]

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