Fully batched seq2seq example based on practical-pytorch, and more extra features.
-
Updated
Mar 11, 2018 - Jupyter Notebook
Fully batched seq2seq example based on practical-pytorch, and more extra features.
A simple program on how you can use tensor-board for visualization and how you can freeze your model graph and later use if for testing
Exploring Reinforcement Learning Solutions to the Vehicle Routing Problem. PPO, A2C, DQN, SAC
Deep-Attention Text Classifier in Tensorflow
This repo helps to track model Weights, Biases and Gradients during training with loss tracking and gives detailed insight for Classification-Model Evaluation
Data visualization using Matplotlib, pandas, seaborn and tensorboard
Predicted biomass pyrolysis yields using multilayer perceptron models (ANNs) and RFs.
Classifies the cifar-10 database by using a vgg16 network. Training, predicting and showing learned filters are included.
Supervised binary classification of skin lesions from dermascopic images using an ensemble of diverse CNN architectures (EfficientNet-B4, ResNet-50).
📊 📈 📉 👀 Graph Visualization using Tensorboard
Embedding Visualization in TensorBoard
Калькулятор "идеальной" эпохи по данным из графиков Tenserboard
Example of how to use TensorBoard in TensorFlow
Consists of variety of Autoencoders implementation for various applications such as denoising image, reverse image search, segmantic hair segmentation.
TF Reader is an offline alternative to TensorBoard that offers a more thorough division of Scalars and custom plots, with a tkinter GUI and matplotlib. It scans training folders, identifies sessions by model/reward tags, size, and supports curve smoothing via slider, but currently only plots Scalars.
Add a description, image, and links to the tensorboard-visualization topic page so that developers can more easily learn about it.
To associate your repository with the tensorboard-visualization topic, visit your repo's landing page and select "manage topics."