Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

Abstract: In this study, a classification hybrid model for the recognition of seven different types of gemstones is developed by using CNNs and KNN. The model classifies Kyanite, Emerald, Coral, ...

Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...

In this study, we developed a dataset of behaviors associated with lameness in dairy cows. The data collection utilized IoT collars that were placed around the necks of 10 dairy cows. This publicly ...

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Abstract: The vehicle classification in congested traffic is a big challenge due to the difficulty to segment packs of different vehicles that stand still next to each other or travel at a very low ...

1 Department of Computer Studies, Arab Open University, Riyadh, Saudi Arabia 2 Department of Computer Sciences, ISSAT, University of Gafsa, Gafsa, Tunisia Cybersecurity has become a significant ...

In this tutorial, we demonstrate how to efficiently fine-tune the Llama-2 7B Chat model for Python code generation using advanced techniques such as QLoRA, gradient checkpointing, and supervised ...