Deep Learning with Yacine on MSN

Visualizing High-Dimensional Data Using PCA in Scikit-Learn

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and ...
SciELO

Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach

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 ...
IEEE

Secure kNN for Distributed Cloud Environment Using Fully Homomorphic Encryption

Abstract: Privacy-preserving k-nearest neighbor (PPkNN) classification for multiple clouds enables categorizing queried data into a class in keeping with data privacy ...
Semiconductor Engineering

Using AI For Fault Detection And Classification In Manufacturing

Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot ...
Hosted on MSN

Sleep Classification with Python – EEG, Sklearn and MNE – Part 1

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!
Frontiers

A hierarchical multi-class classification system for face and text datasets

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...
Scientific Research Publishing

An Evaluation of Machine Learning Models for Threat Classification in IoT Devices ()

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
Frontiers

KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...
IEEE

Automatic Scikit-learn based detection and classification of Breast Cancer using Machine./ Learning techniques

Abstract: The most severe disease nowadays is breast cancer. The abnormal development of breast cells is what causes breast cancer. The breast ducts may include this type of malignancy. Women over 40 ...
marktechpost

Fine-Tuning of Llama-2 7B Chat for Python Code Generation: Using QLoRA, SFTTrainer, and Gradient Checkpointing on the Alpaca-14k Dataset

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 ...