Machine Learning For Time-Series With Python By Ben Auffarth 2021

Machine Learning For Time-Series With Python By Ben Auffarth 2021

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Machine Learning For Time-Series With Python By Ben Auffarth 2021

In this post, we will explore the fascinating world of time-series analysis using machine learning techniques with Python. Ben Auffarth, a seasoned data scientist and machine learning expert, will guide us through the process of building predictive models for time-series data.

Time-series data is everywhere – from stock prices and weather forecasts to sensor readings and customer behavior. Understanding and predicting patterns in time-series data can provide valuable insights for businesses and organizations.

Ben Auffarth will walk us through the steps of preprocessing time-series data, selecting the right machine learning algorithms, and evaluating our models for accuracy and performance. We will cover popular algorithms such as ARIMA (AutoRegressive Integrated Moving Average), LSTM (Long Short-Term Memory), and Prophet.

By the end of this post, you will have a solid foundation in using machine learning for time-series analysis with Python. Whether you are a beginner looking to learn the basics or an experienced data scientist seeking to expand your skill set, this post is for you.

Stay tuned for actionable insights, practical examples, and hands-on tutorials from Ben Auffarth on Machine Learning For Time-Series With Python in 2021.
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