Distributed Fast Fourier Transform in TensorFlow
Posted by Ruijiao Sun, Google Intern – DTensor team Fast Fourier Transform is an important method of signal processing, which is commonly used in a…
Tag: TensorFlow
Scikit-Learn vs TensorFlow: Which One to Choose?
The landscape of machine learning and artificial intelligence has been revolutionized by powerful libraries that redefine model creation and utilizati…
LLaMA in R with Keras and TensorFlow
Implementation and walk-through of LLaMA, a Large Language Model, in R, with TensorFlow and Keras.
TensorFlow Hub ❤️ Kaggle
Posted by Luiz GUStavo Martins, Google AI Developer Advocate We’re excited to announce our new integration with Kaggle Models, a recently launched pre-trained model platform.…
TensorFlow Datasets is turning 4!
Posted by the TensorFlow Datasets team Datasets landscape has changed a lot since TensorFlow Datasets (TFDS) was introduced about 4 years ago: TFDS made sharing…
JAX vs Tensorflow vs Pytorch: Building a Variational Autoencoder (VAE)
A side-by-side comparison of JAX, Tensorflow and Pytorch while developing and training a Variational Autoencoder from scratch
A first look at federated learning with TensorFlow
The term "federated learning" was coined to describe a form of distributed model training where the data remains on client devices, i.e., is never shi…
NumPy-style broadcasting for R TensorFlow users
Broadcasting, as done by Python's scientific computing library NumPy, involves dynamically extending shapes so that arrays of different sizes may be p…
First experiments with TensorFlow mixed-precision training
TensorFlow 2.1, released last week, allows for mixed-precision training, making use of the Tensor Cores available in the most recent NVidia GPUs. In t…
