Faktion Academy.
Machine Learning for sensor data
This course will teach best practices on deploying ML models, model management, data versioning and useful frameworks to use.
Course outline
General concepts
- Sampling theorem
- Time windows and aggregation
- Data splitting for time series data
- Common data quality problems and how to solve them
- Aligning flow by using dynamic time warping
- Digital Twins
Pre-processing sensor data time series
- Interpolation
- Noise reduction
- Outlier detection
- Dimensionality reduction
- Dealing with mixed sample frequencies
Feature calculation
- Why?
- Autocorrelation
- Fourier transformations
- Peak detection
- ARIMA models
Forecasting (on demand)
- Arima models
- Exponential smoothing models
- Anomaly detection based on forecasting
Predictive maintenance (on demand)
- Predictive maintenance and survival function estimation
- Kaplan Meier estimators
- Cox Proportional Hazard model
- Aalen Additive Hazard model
- Time series similarity kernel regression
Deep Learning for sensor data (on demand)
- Recurrent architectures
- Convolutional architectures
- Anomaly detection based on auto-encoders
- Reinforcement learning for optimal control
- Differential evolution
- Surrogate/Bayesian optimization
Case studies and exercises will take place per chapter.
The course outline will be tailored to the participant’s wishes and needs.
Course level
Expert
Prerequisites
- Python programming at the intermediate level
- Knowledge of basic Machine Learning concepts like data splitting, classification, overfitting, probabilities, …
Course teachers
Jeroen Boeye, PhD
Head of Sensor Data
Vladimir Dzyuba, PhD
Senior ML Engineer
Course fee
EUR 3.000 excl. VAT
Included in course package
- Course material
- Drinks, snacks and lunch
- Cloud servers for use during training
- 4h of support and question answering up to 6 months after the course
“
The Natural Language Processing course was a perfect balance between a summary view of the NLP journey with its modelling approaches over time and some technical details, plus a practical business view on real-world applications.
Claudia Burgard
Senior Data Scientist at Stepstone
Register now – limited seats
Machine Learning for Sensor Data
8-10/09/2020
We will confirm your registration by e-mail
