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Course Outline
Current state of the technology
- What is used
- What may be potentially used
Rules based AI
- Simplifying decision
Machine Learning
- Classification
- Clustering
- Neural Networks
- Types of Neural Networks
- Presentation of working examples and discussion
Deep Learning
- Basic vocabulary
- When to use Deep Learning, when not to
- Estimating computational resources and cost
- Very short theoretical background to Deep Neural Networks
Deep Learning in practice (mainly using TensorFlow)
- Preparing Data
- Choosing loss function
- Choosing appropriate type on neural network
- Accuracy vs speed and resources
- Training neural network
- Measuring efficiency and error
Sample usage
- Anomaly detection
- Image recognition
- ADAS
Requirements
The participants must have programming experience (any language) and engineering background, but are not required to write any code during the course.
14 Hours
Testimonials (1)
A real presentation of knowledge representing methods used by real AUTOSAR specialists in the automotive industry.
Bartlomiej - BorgWarner Poland Sp. z o.o.
Course - Autosar Introduction – Technology Overview
Machine Translated