Our live TensorFlow training sessions, available online or onsite, combine interactive discussions with hands-on practice to illustrate how to effectively utilize the TensorFlow framework for machine learning research. This approach simplifies the transition from experimental research prototypes to robust production systems.
Training is offered as either "online live training" or "onsite live training." Online live training, also known as "remote live training," is delivered through an interactive remote desktop environment. Onsite live training can be conducted directly at your premises in Prague or at NobleProg’s corporate training centers in Prague.
From Prague Main Train Station (Praha hlavní nádraží)
Take tram 9 from Hlavní nádraží toward Sídliště Řepy.
Get off at Újezd.
Walk about 10 minutes toward Malostranské náměstí / Prokopská.
Continue along Prokopská to 296/8.
Alternative: Take the metro C from Hlavní nádraží → Muzeum, change to metro A → Malostranská, then walk across Malá Strana. This involves more walking.
From Prague Bus Station — Florenc
Take metro B from Florenc toward Zličín.
Get off at Můstek.
Change to metro A toward Nemocnice Motol.
Get off at Malostranská.
Walk approximately 10–15 minutes to Prokopská 296/8.
This instructor-led, live training in Prague (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 Prague (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 Prague (online or on-site) targets data scientists who wish to utilize TensorFlow to analyze potential fraud data.
By the end of this training, participants will be able to:
Create a fraud detection model in Python and TensorFlow.
Build linear regressions and linear regression models to predict fraud.
Develop an end-to-end AI application for analyzing fraud data.
This instructor-led live training in Prague (available online or on-site) is designed for developers and data scientists who aim to utilize TensorFlow 2.x for building predictors, classifiers, generative models, and neural networks.
By the end of this training, participants will have the capability to:
Install and configure TensorFlow 2.x.
Understand the benefits of TensorFlow 2.x over previous iterations.
Build deep learning models.
Implement advanced image classifiers.
Deploy deep learning models to cloud, mobile, and IoT platforms.
This 35-hour course in Prague delves into the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Participants will gain hands-on proficiency with Theano and TensorFlow, acquiring the skills to build, train, and deploy production-grade deep learning models for real-world scenarios.
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Testimonials (1)
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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