Du lette etter:

python tensorflow keras

Module: tf.keras.layers | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › layers
Public API for tf.keras.layers namespace. ... TensorFlow Core v2.7.0 · Python. Was this helpful? ... Input() is used to instantiate a Keras tensor.
Module: tf.keras.utils | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › utils
Public API for tf.keras.utils namespace. ... set_random_seed(...) : Sets all random seeds for the program (Python, NumPy, and TensorFlow).
The Sequential model | TensorFlow Core
https://www.tensorflow.org › keras
import tensorflow as tf from tensorflow import keras from tensorflow.keras import layers. When to use a Sequential model. A Sequential model is appropriate ...
Keras: the Python deep learning API
keras.io
Keras is a central part of the tightly-connected TensorFlow 2 ecosystem, covering every step of the machine learning workflow, from data management to hyperparameter training to deployment solutions. State-of-the-art research.
How to correctly install Keras and Tensorflow - ActiveState
https://www.activestate.com/.../how-to-install-keras-and-tensorflow
06.12.2021 · Because Keras is a high level API for TensorFlow, they are installed together. In general, there are two ways to install Keras and TensorFlow: Install a Python distribution that includes hundreds of popular packages (including Keras and TensorFlow) such as ActivePython. Use pip to install TensorFlow, which will also install Keras at the same time.
TensorFlow - Keras - RxJS, ggplot2, Python Data ...
https://www.tutorialspoint.com/tensorflow/tensorflow_keras.htm
TensorFlow - Keras. Keras is compact, easy to learn, high-level Python library run on top of TensorFlow framework. It is made with focus of understanding deep learning techniques, such as creating layers for neural networks maintaining the concepts of shapes and mathematical details. The creation of freamework can be of the following two types −.
Module: tf.keras.applications | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › applica...
Public API for tf.keras.applications namespace. ... TensorFlow Core v2.7.0 · Python. Was this helpful? Module: tf.keras.applications. On this page
python - Tensorflow compatibility with Keras - Stack Overflow
stackoverflow.com › questions › 62690377
Jul 02, 2020 · python tensorflow keras version compatibility. Share. Follow edited Mar 4 '21 at 1:57. Scott. 3,157 3 3 gold badges 28 28 silver badges 48 48 bronze badges.
How to Predict Stock Prices in Python using TensorFlow 2 and ...
www.thepythoncode.com › article › stock-price
Predicting different stock prices using Long Short-Term Memory Recurrent Neural Network in Python using TensorFlow 2 and Keras. Abdou Rockikz · 24 min read · Updated sep 2021 · Machine Learning · Finance
Module: tf.keras | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › keras
Public API for tf.keras namespace. ... TensorFlow Core v2.7.0 · Python. Was this helpful? Module: tf.keras. On this page
tf.keras.Model | TensorFlow Core v2.7.0
https://www.tensorflow.org › api_docs › python › Model
Model groups layers into an object with training and inference features.
How to correctly install Keras and Tensorflow - ActiveState
www.activestate.com › resources › quick-reads
Dec 06, 2021 · Because Keras is a high level API for TensorFlow, they are installed together. In general, there are two ways to install Keras and TensorFlow: Install a Python distribution that includes hundreds of popular packages (including Keras and TensorFlow) such as ActivePython. Use pip to install TensorFlow, which will also install Keras at the same time.
About Keras
https://keras.io › about
Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast ...
TensorFlow - Keras - Tutorialspoint
www.tutorialspoint.com › tensorflow_keras
TensorFlow - Keras. Keras is compact, easy to learn, high-level Python library run on top of TensorFlow framework. It is made with focus of understanding deep learning techniques, such as creating layers for neural networks maintaining the concepts of shapes and mathematical details. The creation of freamework can be of the following two types −.
Keras: the Python deep learning API
https://keras.io
Keras is a central part of the tightly-connected TensorFlow 2 ecosystem, covering every step of the machine learning workflow, from data management to hyperparameter training to deployment solutions. State-of-the-art research.
TensorFlow 2 Tutorial: Get Started in Deep Learning With tf ...
https://machinelearningmastery.com › ...
Using tf.keras allows you to design, fit, evaluate, and use deep learning models to make predictions in just a few lines of code. It makes ...