Online TensorFlow Training in South Korea

This instructor-led, live training in South Korea (online or onsite) is designed for advanced-level professionals seeking 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 South Korea (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.

Target Audience

This course is designed for researchers and engineers in the field of deep learning who wish to leverage available tools, primarily open-source solutions, for the analysis of visual data.

The curriculum includes practical, working examples.

This instructor-led, live training (online or onsite) is designed for data scientists who want to use 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 South Korea (online or onsite) is designed for developers and data scientists who want to use TensorFlow 2.x to build predictors, classifiers, generative models, neural networks, and more.

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

• Install and configure TensorFlow 2.x.
• Understand the advantages of TensorFlow 2.x over previous versions.
• Construct deep learning models.
• Implement an advanced image classifier.
• Deploy deep learning models to the cloud, mobile devices, and IoT devices.

This course provides foundational knowledge of neural networks and their broader role within machine learning and deep learning algorithms and applications.

The first segment (40%) of the training emphasizes core fundamentals, equipping you to select appropriate technologies such as TensorFlow, Caffe, Theano, DeepDrive, and Keras.

The second segment (20%) introduces Theano, a Python library designed to simplify the development of deep learning models.

The third segment (40%) focuses extensively on TensorFlow, the open-source software library for deep learning developed by Google. All examples and hands-on exercises will be conducted using TensorFlow.

Audience

This course is designed for engineers aiming to utilize TensorFlow for their deep learning projects.

Upon completion, participants will:

• gain a solid understanding of deep neural networks (DNN), CNNs, and RNNs
• comprehend the structure and deployment mechanisms of TensorFlow
• possess the skills to manage installation, production environment setup, architecture tasks, and configuration
• be capable of assessing code quality, performing debugging, and monitoring systems
• be able to implement advanced production-level tasks, including model training, graph construction, and logging