Pythonによる時系列分析~機械学習・ディープラーニング編

Master Time Series Forecasting with Python: A Practical Guide

Unlock the power of predicting future trends with time series forecasting using Python! This course focuses on practical application, guiding you through real-world scenarios rather than getting bogged down in complex algorithms.

What you'll learn:

• Fundamentals of Time Series Forecasting: Understand the core concepts and importance of analyzing temporal data.
• Time Series Data Characteristics: Explore the unique properties of time series data and how they impact forecasting.
• Key Techniques: We'll cover a range of methods, with a strong emphasis on:
  • Machine Learning for Time Series: Learn how to apply machine learning models to predict future values.
  • Deep Learning for Time Series: Dive into deep learning techniques for advanced forecasting.
  • Prophet: Utilize Facebook's Prophet library for robust time series forecasting.
  • Fourier Transform: Understand and apply Fourier analysis for time series decomposition.
• Practical Problem Setting: Focus on defining the right forecasting problem and choosing the appropriate approach for your needs.
• Actionable Insights: Discover how to interpret your forecasts and make data-driven decisions.

Course Highlights:

• Hands-on Google Colaboratory: All code and exercises are designed to run seamlessly in Google Colaboratory.
• Keras for Deep Learning: Leverage the Keras library for building and training deep learning models.
• Focus on Application: We prioritize practical application over deep theoretical dives. This course is designed for those who want to do time series forecasting.

Who is this course for?

• Beginners: You have basic Python skills and are eager to start working with time series forecasting.
• Professionals: You need to apply time series forecasting in your job.

Important Notes:

• While we strive for a smooth learning experience, troubleshooting and independent research are encouraged.
• This course does not delve into the intricate details of individual deep learning algorithms or advanced optimization techniques.
• Not for NLP: This course focuses solely on time series data and does not cover natural language processing (NLP).
• Experienced Practitioners: If you are already proficient in time series forecasting, this course may not be the best fit. Please consider carefully before enrolling.

Get ready to transform raw time series data into valuable predictions!