Training: TensorFlow
Level
AdvancedDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedTraining: TensorFlow
The TensorFlow training is an intensive two-day course focused on the practical application of this popular machine learning framework. The program is designed to provide participants with a solid theoretical foundation (20%) while dedicating the majority of the time (80%) to hands-on workshops and projects. The course is intended for individuals who want to deepen their knowledge of artificial intelligence and machine learning, particularly with TensorFlow.
What will you learn?
- How to install and configure TensorFlow in your working environment
- How to build, train, and optimize machine learning models with TensorFlow
- How to implement advanced neural networks, such as CNNs
- How to prepare and deploy TensorFlow models in production environments
Important information before the training
- Basic knowledge of Python programming
- Basic knowledge of machine learning
- Ability to work in Jupyter Notebook or Google Colab environments
Who is this training for?
Developers and data engineers who want to expand their skills with TensorFlow-
Data scientists seeking to apply TensorFlow in their projects
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AI and ML enthusiasts who want to start working with TensorFlow
Training Program
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Day 1: Introduction to TensorFlow and Machine Learning Fundamentals
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Introduction to TensorFlow
- History and development of TensorFlow
- Architecture and main components
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Installation and environment setup
- Installing TensorFlow and dependencies
- Setting up the environment (Jupyter Notebook, Colab)
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TensorFlow basics
- Operations, tensors, and variables
- Building and running simple models
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Workshop: Building your first model
- Implementing a simple linear model
- Training and evaluating the model on a dataset
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Introduction to Keras
- History and development of Keras
- Architecture and main components
- Integrating Keras with TensorFlow
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Day 2: Advanced Techniques and Practical Applications
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Advanced models in TensorFlow and Keras
- Neural networks and their architecture
- Implementing and training Convolutional Neural Networks (CNNs)
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Model optimization and fine-tuning
- Optimization and regularization techniques
- Fine-tuning pretrained models
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Workshop: Building an image classification model
- Preparing and processing image data
- Implementing and training a CNN for image classification with Keras
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Deploying TensorFlow and Keras models
- Exporting models and preparing them for deployment
- Practical aspects of deploying models in production environments
