Why TensorFlow “TensorFlow™ is an open source software library for numerical computation using data flow graphs.” One of many frameworks for deep learning computations Scalable and flexible Popular (= … To follow this tutorial, run the notebook in Google Colab by clicking the button at the top of this page. Deep learning is a subfield of machine learning that is a set of algorithms that is inspired by the structure and function of the brain.
For that, I recommend starting with this excellent book. Si vous souhaitez une suite de tutoriels gratuits, en français, sur TensorFlow 2.x, alors consultez notre site https://tensorflow.backprop.fr et inscrivez-vous (gratuitement encore) pour des articles complémentaires qui pourront vous conduire aussi loin que la certification. Google's TensorFlow is an open-source and most popular deep learning library for research and production. TensorFlow est un outil open source d'apprentissage automatique développé par Google. Le kit de TensorFlow se compose des deux composants suivants : Un Protocol Buffer pour le graphe; Un environnement d'exécution qui exécute le graphe (distribué) Ces deux composants sont analogues au compilateur Java et à la machine virtuelle Java (JVM). TensorFlow est une plate-forme logicielle permettant de créer des modèles de machine learning (ML). TensorFlow Tutorial For Beginners. This tutorial is designed to be your complete introduction to tf.keras for your deep learning project.

Run all the notebook code cells: Select Runtime > Run all. The focus is on using the API for common deep learning model development tasks; we will not be diving into the math and theory of deep learning. Learn TensorFlow is a book written by Pramod Singh and Avish Manure. À l'instar de la JVM, le kit de TensorFlow est mis en œuvre sur plusieurs plates-formes matérielles : processeurs et GPU. Learn how to build a neural network and how to train, evaluate and optimize it with TensorFlow. The book also focuses on building Supervised Machine Learning models using TensorFlow. 1) Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python. TensorFlow Tutorial Overview. This course covers basics to advance topics like linear regression, classifier, create, train and evaluate a neural network like CNN, RNN, auto encoders etc. Le code source a été ouvert le 9 novembre 2015 par Google et publié sous licence Apache. In Colab, connect to a Python runtime: At the top-right of the menu bar, select CONNECT. Refer these machine learning tutorial, sequentially, one after the other, for maximum efficacy of learning.