Build logistic regression, neural network models for classification
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Updated
Jan 31, 2019
Build logistic regression, neural network models for classification
[BMVC'23 Oral] Offical repository of "Rethinking Transfer Learning for Medical Image Classification"
Source code for the numerical experiments presented in the paper "Greedy Shallow Networks: An Approach for Constructing and Training Neural Networks".
In recent times, toxicological classification of chemical compounds is considered to be a grand challenge for pharma-ceutical and environment regulators. Advancement in machine learning techniques enabled efficient toxicity predic-tion pipelines. Random forests (RF), support vector machines (SVM) and deep neural networks (DNN) are often ap-plied…
Libreria didattica per la creazione, addestramento e test di reti neurali fino a tre strati in linguaggio C
Predicting if a mushroom is edible or poisonous with a shallow neural network with Keras and TensorFlow 2.
[NeurReps 2024, TMLR 2025] Can Kernel Methods Explain How the Data Affects Neural Collapse?
Notebooks of programming assignments of Neural Networks and Deep Learning course of deeplearning.ai on coursera in August-2019
Deep learning Specialization on Coursera
Logistic Regression Implementations - ML, Shallow NN and Enhanced Deep Neural Network for Structured and Unstructured Data Classification
Human Data Analytics (Optional Project)
Comparative Analysis of Activation Functions in Shallow Neural Networks for Multi-Class Image Classification Using MNIST Digits and CIFAR-10 Datasets with Fixed Architectural Parameters
This is a project that is derived from my capstone project targeted for cleaning of EEG signals and feature extraction followed by a custom made neural network and analysis of performance by the Network mainly for classifying the valence of an emotion.
A shallow CNN model that is trained on X-ray chest images with preprocessing step of adaptive histogram equalization.
High-throughput detection and enumeration of tumor cells in blood using Digital Holographic Microscopy (DHM) and Deep Learning.
study of scene classification with different MLP layer types
In this project, we propose a cervical cancer detection and classification system using CNNs . We employ transfer learning and fine-tuning for enhanced performance. Classifiers like ELM and AE are added to increase the efficiency.
Car Price Prediction is a machine learning project aimed at developing a model that can predict the selling price of used cars based on various features or attributes.
Challenge of shallow neural network approximation with one-dimensional input.
Design of an one hidden layer neural network using numpy only,
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