There are 1 repository under softmax-classification topic.
Multi-language Analyze text in 26 Cantonal Swiss German, Italian, German, Chinese (simplified), French, Italian. pply natural language understanding (NLU) to their applications with features including sentiment analysis, entity analysis, entity sentiment analysis, content classification, and syntax analysis.
MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20
Official repository for ElasticFace: Elastic Margin Loss for Deep Face Recognition
【武汉大学遥感学院】空间智能感知与服务课设 | 基于Softmax的多波段遥感影像分类
Plots how the logit values that are passed into the softmax function change over time as the model is trained.
Multiclass Classification using Softmax from scratch without any famous library like Tensorflow, Pytorch, etc.
A repository for hosting some of the popular machine learning algorithm implementations.
Implementing deep learning algorithms from scratch
These Codes are written as part of Neural Networks and Deep learning course at UCLA.
handwritten digit recognition in real time
About some methods in Deep Learning using TensorFlow
A deep learning model that recognizes hand gestures for alphabets. Trained using tensorflow, with activation function : RELU and Softmax (for multi-class classification).
It reads handwritten numbers given an input of pixel values. A supervised learning, gradient descent, mini-batching, softmax-output-activation neural network that is meant to be trained on the MNIST dataset (dataset not included in this repository).
Push features to OSM taked from satellite images.
Applying Convolutional Neural Networks (CNN) for recognizing manuscript digits.
"This program trains a model using 'SVM' or 'Softmax' and predicts the input data. Loss history and predicted tags are displayed as results."
This is the code for "predict MNIST datasets using pure Tensorflow and Keras, a shallow learning model" By M.Junaid Fiaz
Some deep learning projects using TensorFlow
Neural Network from Scratch with Python