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Introducing Keras 3 for R

We are thrilled to introduce {keras3}, the next version of the Keras R package. {keras3} is a ground-up rebuild of {keras}, maintaining the beloved features of the original while refining and simplifying the API based on valuable insights gathered over the past few years

Keras

Introducing Keras 3 for R

LLaMA in R with Keras and TensorFlow

TensorFlow and Keras 2.9

Deep Learning with R, 2nd Edition

Pre-processing layers in keras: What they are and how to use them

Revisiting Keras for R

An introduction to weather forecasting with deep learning

Training ImageNet with R

FNN-VAE for noisy time series forecasting

Time series prediction with FNN-LSTM

Deep attractors: Where deep learning meets chaos

Easy PixelCNN with tfprobability

Hacking deep learning: model inversion attack by example

Towards privacy: Encrypted deep learning with Syft and Keras

A first look at federated learning with TensorFlow

NumPy-style broadcasting for R TensorFlow users

First experiments with TensorFlow mixed-precision training

Differential Privacy with TensorFlow

tfhub: R interface to TensorFlow Hub

Gaussian Process Regression with tfprobability

Getting started with Keras from R - the 2020 edition

Variational convnets with tfprobability

tfprobability 0.8 on CRAN: Now how can you use it?

TensorFlow 2.0 is here - what changes for R users?

BERT from R

So, how come we can use TensorFlow from R?

Image segmentation with U-Net

Modeling censored data with tfprobability

TensorFlow feature columns: Transforming your data recipes-style

Adding uncertainty estimates to Keras models with tfprobability

Hierarchical partial pooling, continued: Varying slopes models with TensorFlow Probability

Tadpoles on TensorFlow: Hierarchical partial pooling with tfprobability

Experimenting with autoregressive flows in TensorFlow Probability

Auto-Keras: Tuning-free deep learning from R

Getting into the flow: Bijectors in TensorFlow Probability

Audio classification with Keras: Looking closer at the non-deep learning parts

Discrete Representation Learning with VQ-VAE and TensorFlow Probability

Getting started with TensorFlow Probability from R

Concepts in object detection

Entity embeddings for fun and profit

You sure? A Bayesian approach to obtaining uncertainty estimates from neural networks

Naming and locating objects in images

Representation learning with MMD-VAE

Winner takes all: A look at activations and cost functions

More flexible models with TensorFlow eager execution and Keras

Collaborative filtering with embeddings

Image-to-image translation with pix2pix

Attention-based Image Captioning with Keras

Neural style transfer with eager execution and Keras

Getting started with deep learning in R

Generating images with Keras and TensorFlow eager execution

Attention-based Neural Machine Translation with Keras

Classifying physical activity from smartphone data

Predicting Sunspot Frequency with Keras

Simple Audio Classification with Keras

lime v0.4: The Kitten Picture Edition

Machine Learning with R and TensorFlow

Deep Learning for Cancer Immunotherapy

Predicting Fraud with Autoencoders and Keras

Analyzing rtweet Data with kerasformula

Deep Learning With Keras To Predict Customer Churn

Classifying Duplicate Questions from Quora with Keras

Word Embeddings with Keras

Time Series Forecasting with Recurrent Neural Networks

Image Classification on Small Datasets with Keras

Deep Learning for Text Classification with Keras

Keras for R