Author: Deep Learner

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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Artificial intelligence Leave a comment

LoftQ: Reimagining LLM fine-tuning with smarter initialization

This research paper was presented at the 12th International Conference on Learning Representations (opens in new tab) (ICLR 2024), the premier conference dedicated to the advancement of deep learning. Large language models (LLMs) use extensive datasets and advanced algorithms to generate nuanced, context-sensitive content. However, their development requires substantial computational resources. To address this, we developed LoftQ, an innovative technique that streamlines the fine-tuning process—which is used to  

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Python

Python News: What’s New From April 2024

In April 2024, Python’s core development team released versions 3.13.0a6 and 3.12.3 of the language! The former received several exciting features, improvements, and optimizations, while the latter got more than 300 commits for security improvements and bug fixes. The 3.13.0a6 release is the last alpha release. In the first half of May, the code will be frozen and won’t accept new features. Note that 3.13.0a6 is a pre-release, so you shouldn’t use it for production environments. However, it provides a […]

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