Autoencoders with Tensorflow
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Updated
Mar 21, 2018 - Jupyter Notebook
Autoencoders with Tensorflow
MNISTを使った機械学習
Convolutional Neutral Network on MNIST fashion Dataset using Keras (Python)
👗 NN for clothing recognition.
Project assignment for my neural network class
Practice implementation of CNN based multi-class classification on FashionMNIST & CIFAR10 Datasets
CNN to classify fashion clothing items
NN classifier in pytorch for fashion-MNIST dataset
Image Classification in Fashion MNIST dataset using CNN(PyTorch)
TensorFlow CNN for Fashion-MNIST dataset
Implementation of a convolutional neural network model, to classify images of clothing, using the Fashion-MNIST dataset built by Keras, Python.
Academic project (Deep Learning)
using the data set from mnist and different models like decision-tree,svm,logistic regression to analyze the best model that can fit with data set
This GitHub repo contains a collaborative Jupyter notebook showcasing a classification model for the Fashion-MNIST dataset. The notebook includes code snippets and visualizations demonstrating data preparation, model creation, and evaluation. The Fashion-MNIST dataset consists of 70,000 grayscale images of 10 different fashion categories.
Implementation of CNN architectures on the Fashion MNIST dataset using Keras.
Convolutional Neural Networks in Python with Keras
Small experimental code based on tensorflow2&python3.7 during a deep learning course at the UCAS.(mnist;fashion_mnist .etc)
Machine Learning test scripts in Python developed during research in Masters Degree project. Includes TensorFlow 2, Keras, Optuna, Inception Modules, etc
TensorFlow/Keras implementation of Fashion MNIST Dataset
Fashion Mnist Classification (Linear,SVM,CNN)
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