Introducing our Course Feature Engineering for Time Series Forecasting скачать в хорошем качестве

Introducing our Course Feature Engineering for Time Series Forecasting

In this course, you'll learn to extract useful features from time series data to forecast future values using traditional machine learning models like linear regression and xgboost. This course covers: 1️⃣ Core Time Series Concepts: Grasp the fundamentals, including trends, seasonality, and stationarity, to build a solid understanding of your data. 2️⃣ Feature Extraction Techniques: Create lag features, window features using rolling statistics, and cumulative metrics to enhance model accuracy. 3️⃣ Advanced Tools & Strategies: Delve into Fourier transforms, domain-specific features, and external variables for sophisticated forecasting. 4️⃣ Practical Python Coding: Implement all techniques with hands-on coding using Python and libraries like Pandas, Statsmodels, and Scikit-learn, ensuring you can apply them to real-world datasets. 5️⃣ Model-Ready Pipelines: Learn to streamline feature engineering processes, preparing your data for machine learning and deep learning models. Whether you're an aspiring data scientist, machine learning practitioner, or analyst looking to optimize your forecasting workflows, this course will provide you with the tools and confidence to excel in time series modeling. Enroll now: https://www.trainindata.com/p/feature...