Time Series II

The course is intended for people who want to deepen their knowledge and experience in the field of time series analysis.

• basic knowledge of programing in Python
• high school level of mathematics
• Knowledge of machine learning on the level of our course Time Series

• Advanced feature preprocessing
• Classification/pattern detection in sound data
  • Short-time Fourier transformation
  • CNN for sound classification: spectrogram as an image
  • LSTM & CNN combination
  • Example: Speech detection using neural networks
• Time series prediction from textual features
  • Data preprocessing
    • Sentence & word tokenization
    • Model-based vs. dictionary-based word embeddings
    • Of-the-shelf pre-trained word-embeddings models
  • Pre-training with auxiliary classification tasks
  • Model combination & fine-tune training
  • Example: Time series predictions using sentiment analysis of news data

Previous courses

Time Series [MLC_TISE]

Python I - introduction to programming [PYTHON_INTRO]