TensorFlow Training in Plovdiv

This live, instructor-led training in Plovdiv (online or onsite) is aimed at experienced 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 Plovdiv (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 Plovdiv (online or on-site) targets data scientists aiming to utilize TensorFlow for analyzing potential fraud data.

By the conclusion of this training, participants will be able to:

• Build a fraud detection model using Python and TensorFlow.
• Implement linear regressions and models to predict fraud.
• Develop a complete AI application for fraud data analysis.

This instructor-led, live training course in Plovdiv, delivered either online or on-site, is designed for developers and data scientists aiming to utilize TensorFlow 2.x for building predictors, classifiers, generative models, neural networks, and other complex systems.

By the end of this training, participants will be equipped to:

• Install and configure the TensorFlow 2.x environment.
• Understand the key benefits of TensorFlow 2.x over previous versions.
• Construct deep learning models from scratch.
• Implement advanced image classification solutions.
• Deploy deep learning models to cloud infrastructure, mobile platforms, and IoT devices.