Python

HTML and CSS Foundations for Python Developers

When you want to build websites as a Python programmer, there’s no way around HTML and CSS. Almost every website on the Internet is built with HTML markup to structure the page. To make a website look nice, you can style HTML with CSS. If you’re interested in web development with Python, then knowing HTML and CSS will help you understand web frameworks like Django and Flask better. But even if you’re just getting started with Python, HTML and CSS […]

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Search and information retrieval Leave a comment

RASCAL: Novel robotics for scalable and highly available automated storage and retrieval

This research paper was presented at the 41st IEEE International Conference on Robotics and Automation (opens in new tab) (ICRA 2024), the premier international forum for robotics research. Over the past decade, robotics has revolutionized numerous industries that rely on storage systems, such as manufacturing and warehousing. In these contexts, robotics streamlines operations and increase efficiency, and automated storage and retrieval systems (ASRS) are at the heart of this technological shift,  

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Python

What Is the __pycache__ Folder in Python?

When you develop a self-contained Python script, you might not notice anything unusual about your directory structure. However, as soon as your project becomes more complex, you’ll often decide to extract parts of the functionality into additional modules or packages. That’s when you may start to see a __pycache__ folder appearing out of nowhere next to your source files in seemingly random places: project/ │ ├── mathematics/ │ │ │ ├── __pycache__/ │ │ │ ├── arithmetic/ │ │ ├── […]

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MachineLearning Leave a comment

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

Introduction In this post, we will see various ways of doing image subtraction in Python by using NumPy, OpenCV, and Pillow libraries. The subtraction of images may sound a bit strange to beginners but images consist of numeric pixels hence we can perform pixel-wise subtraction between two images. Subtraction of Images When one image is subtracted from another it does pixel-wise subtraction where the pixel of the 2nd image is subtracted from the 1st image resulting in a new 3rd […]

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Artificial intelligence Leave a comment

MatterSim: A deep-learning model for materials under real-world conditions

In the quest for groundbreaking materials crucial to nanoelectronics, energy storage, and healthcare, a critical challenge looms: predicting a material’s properties before it is even created. This is no small feat, with any combination of 118 elements in the periodic table, and the range of temperatures and pressures under which materials are synthesized and operated. These factors drastically affect atomic interactions within materials, making accurate property prediction and behavior simulation exceedingly demanding. Here at Microsoft  

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Machine Learning

How to Use Stable Diffusion Effectively

From the prompt to the picture, Stable Diffusion is a pipeline with many components and parameters. All these components working together creates the output. If a component behave differently, the output will change. Therefore, a bad setting can easily ruin your picture. In this post, you will see: How the different components of the Stable Diffusion pipeline affects your output How to find the best configuration to help you generate a high quality picture Let’s get started. How to Use […]

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Python

PyTorch vs TensorFlow for Your Python Deep Learning Project

PyTorch vs TensorFlow: What’s the difference? Both are open-source Python libraries that use graphs to perform numerical computations on data in deep learning applications. Both are used extensively in academic research and commercial code. Both are extended by a variety of APIs, cloud computing platforms, and model repositories. If they’re so similar, then how do you decide which one is best for your project? You’ll start by taking a close look at both platforms, beginning with the slightly older TensorFlow. […]

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Python

Flattening a List of Lists in Python

Sometimes, when you’re working with data, you may have the data as a list of nested lists. A common operation is to flatten this data into a one-dimensional list in Python. Flattening a list involves converting a multidimensional list, such as a matrix, into a one-dimensional list. In this video course, you’ll learn how to do that in Python. What’s Included: Downloadable Resources:    

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