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Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation

(ebook) (audiobook) (audiobook) Książka w języku 1
Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation Tarek A. Atwan - okladka książki

Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation Tarek A. Atwan - okladka książki

Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation Tarek A. Atwan - audiobook MP3

Time Series Analysis with Python Cookbook. Practical recipes for exploratory data analysis, data preparation, forecasting, and model evaluation Tarek A. Atwan - audiobook CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
630
Dostępne formaty:
     PDF
     ePub
Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting.
This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you’ll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you’ll work with ML and DL models using TensorFlow and PyTorch.
Finally, you’ll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book.

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O autorze książki

Tarek A. Atwan is a data analytics expert with over 16 years of international consulting experience, providing subject matter expertise in data science, machine learning operations, data engineering, and business intelligence. He has taught multiple hands-on coding boot camps, courses, and workshops on various topics, including data science, data visualization, Python programming, time series forecasting, and blockchain at different universities in the United States. He is regarded as an industry mentor and advisor, working with executive leaders in various industries to solve complex problems using a data-driven approach.

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