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Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python free ebook download

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Algorithms

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Author(s):	Akshay R Kulkarni

Date:	2023	Format:	pdf	Language:	English	ISBN/ASIN:	1484289773
Pages:	190	OCR:		Quality:		ISBN13:
Uploader:	gestalt	Upload Date:	1/22/2023 6:23:29 PM

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1484289773 pdf
This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. 
It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive  integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book, you will have a foundational understanding of various concepts relating to time series and its implementation in Python. 
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3169200	Book	https://nitroflare.com/view/066714174E6B...		0.00	gestalt

Tags: Algorithms Deep Implement Learning Machine Python Recipes Techniques Time

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Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python free ebook download

Category: Algorithms

Description: Click to see full description

Category:
Algorithms