Loss function, Neural network, Das Model, Output, Artificial neural network, Machine learning

Introduction to Keras for Researchers

On Oct 2, 2020
@fchollet shared
Based on your feedback, I've updated our "introduction to Keras for researchers" page so that it starts with the basics -- tensors, variables, and gradients -- instead of starting with layers. Check it out: https://t.co/1CI3QtrZ5X
Open

Keras documentation

keras.io
On Oct 2, 2020
@fchollet shared
Based on your feedback, I've updated our "introduction to Keras for researchers" page so that it starts with the basics -- tensors, variables, and gradients -- instead of starting with layers. Check it out: https://t.co/1CI3QtrZ5X
Open

Normalizing Flows in 100 Lines of JAX

Normalizing Flows in 100 Lines of JAX

JAX  is a great linear algebra + automatic differentiation library for fast experimentation with and teaching machine learning. Here is a li...

What is torch.nn really?

What is torch.nn really?

if not (PATH / FILENAME).exists(): content = requests.get(URL + FILENAME).content (PATH / FILENAME).open("wb").write(content) This dataset is in numpy array format, and has been stored ...

A Lightning-Fast Introduction to Deep Learning and TensorFlow 2.0

A Lightning-Fast Introduction to Deep Learning and TensorFlow 2.0

A hands-on guide to getting started with TensorFlow 2.0

Keras FAQ

Keras FAQ

Keras documentation

Training and Evaluation with TensorFlow Keras

Training and Evaluation with TensorFlow Keras

# Generate predictions (probabilities -- the output of the last layer) # on new data using `predict` print('\n# Generate predictions for 3 samples') predictions = model.predict(x_test[:3]) ...

Practical Text Classification With Python and Keras

Practical Text Classification With Python and Keras

Learn about Python text classification with Keras. Work your way from a bag-of-words model with logistic regression to more advanced methods leading to convolutional neural networks. See ...

Haiku: Sonnet for JAX

Haiku: Sonnet for JAX

JAX-based neural network library. Contribute to deepmind/dm-haiku development by creating an account on GitHub.

3 ways to create a Keras model with TensorFlow 2.0 (Sequential, Functional, and Model Subclassing)

3 ways to create a Keras model with TensorFlow 2.0 (Sequential, Functional, and Model Subclassing)

Keras and TensorFlow 2.0 provide you with three methods to implement your own neural network architectures:, Sequential API, Functional API, and Model subclassing. Inside of this tutorial ...

From Exploration to Production — Bridging the Deployment Gap for Deep Learning

From Exploration to Production — Bridging the Deployment Gap for Deep Learning

This article introduces EMNIST, we develop and train models with PyTorch, translate them with the Open Neural Network eXchange format ONNX and serve them through GraphPipe. We will ...

Click here to read the article

Click here to read the article

Typical use cases 10 engine %@% ' function getPartsOfSpeech(text) { var doc = new DocumentClass(text); var list = []; for (i = 0; i < doc.sentences().size(); i++) { var sentence = ...

Google Introduces Flax: A Neural Network Library for JAX

Google Introduces Flax: A Neural Network Library for JAX

Google recently introduce Flax — a neural network library for JAX that is designed for flexibility.