Time Series Classification in Python 🚀

Master machine learning techniques for time series classification, in the most complete course on the subject, through hands-on projects and real-world applications.

👉 Not enrolled? Do it right here

🎯 What You'll Learn

Tackle any time series classification project by learning

• Advanced classification techniques for temporal data
• Flexible blueprint to apply deep learning architectures
• Feature engineering for time series classification
• Visualization techniques for time series data
• Capstone projects with full solutions using real-world applications, like sensor data, healthcare, spectroscopy and more.

💻 Getting Started

Prerequisites

• Python 3.10+
• Anaconda to manage the virtual environment
• Basic understanding of machine learning concepts
• Familiarity with PyTorch or TensorFlow

Environment Setup

1. Clone this repository:

git clone https://github.com/marcopeix/time-series-classification-in-python
cd time-series-classification-in-python

2. Create a virtual environment:

conda env create -f environment.yml

📘 Course Content

This repository contains:

• all starter and solution notebooks for each lesson
• 📁 data/: sample datasets for practice and to download onlide data

🎓 Full Course Access

This repository only makes sense if you are enrolled in the course. By enrolling, you get:

• 6+ hours of video content
• Answers to all your questions
• Certificate of completion
• Lifetime access to course updates

👉 Enroll in the full course

📚 Additional Resources

• Sktime documentation
• Time series classificaton datasets directory

---

⭐️ If you find this repository helpful, please consider starring it!