Delivered either online or on-site, these instructor-led live TensorFlow training courses provide a comprehensive look at the framework. Through interactive discussion and practical exercises, participants will learn how to utilize TensorFlow for machine learning research, ensuring a smooth and efficient transition from experimental prototypes to robust production systems.
The TensorFlow curriculum is offered as both "online live training" and "onsite live training". Online sessions, also referred to as "remote live training", are conducted through an interactive, remote desktop environment. Conversely, onsite live training can be delivered directly on client premises in Nantes or at NobleProg corporate training centers in Nantes.
NobleProg -- Your Local Training Provider
Nantes, Zenith
NobleProg Nantes, 4 rue Edith Piaf, Saint-Herblain, france, 44821
In the Parc d'Ar Mor zone, near the Zénith.
Car : from the ring road, Porte de Chézine Exit> Boulevard du Zenith > Esplanade Georges Brassens (restaurants) > Rue Edith Piaf on the right. From the N444 road (Nantes > Lorient), Exit #1 > boulevard Marcel Paul > Rue Edith Piaf at the right.
Parking Zénith P1 (free). Once parked, you can recognize the building: it's one of the tree bulding with zinc frontage.
Bicycle: free indoor parking
Public transport :
Tramway R1, Schoelcher station + 10 mn by foot through commercial center Atlantis
Tramway R1, François Mitterrand stop + bus 50, stop at Saulzaie station or bus 71, stop at the Zénith station
Tramway R3, Marcel Paul station + bus 50, Saulzaie station
Chronobus C6, Hermeland station+ bus 71, Zénith station
Bus : lignes 50 (Saulzaie station) or 71 (Zénith station)
This instructor-led, live training in Nantes (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.
By the end of this training, participants will be able to:
Build and train convolutional neural networks (CNNs) using TensorFlow.
Leverage Google Colab for scalable and efficient cloud-based model development.
Implement image preprocessing techniques for computer vision tasks.
Deploy computer vision models for real-world applications.
Use transfer learning to enhance the performance of CNN models.
Visualize and interpret the results of image classification models.
This instructor-led, live training in Nantes (online or onsite) is aimed at intermediate-level data scientists and developers who wish to understand and apply deep learning techniques using the Google Colab environment.
By the end of this training, participants will be able to:
Set up and navigate Google Colab for deep learning projects.
Understand the fundamentals of neural networks.
Implement deep learning models using TensorFlow.
Train and evaluate deep learning models.
Utilize advanced features of TensorFlow for deep learning.
This instructor-led live training in Nantes (online or onsite) is designed for developers and data scientists who intend to utilize Tensorflow 2.x for building predictors, classifiers, generative models, and neural networks, among other applications.
Upon completion of this training, participants will be capable of:
Installing and configuring TensorFlow 2.x.
Understanding the advantages of TensorFlow 2.x over earlier versions.
Developing deep learning models.
Implementing an advanced image classifier.
Deploying deep learning models to the cloud, mobile applications, and IoT devices.
This 35-hour course in Nantes explores the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Participants will gain practical experience with Theano and TensorFlow, learning to construct, train, and deploy production-grade deep learning models for real-world scenarios.
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Testimonials (2)
The adaptation of exos to our context and the consideration of our request
Amel Guetat - EURO-INFORMATION DEVELOPPEMENTS
Course - Fraud Detection with Python and TensorFlow
Machine Translated
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
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