{"product_id":"time-series-algorithms-recipes-implement-machine-learning-and-deep-learning-techniques-with-python-9781484289778","title":"Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python","description":"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. \u003cbr\u003eIt 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. \u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eImplement various techniques in time series analysis using Python.\u003c\/li\u003e\n\u003cli\u003eUtilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting \u003c\/li\u003e\n\u003cli\u003eUnderstand univariate and multivariate modeling for time series forecasting\u003c\/li\u003e\n\u003cli\u003eForecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory)\u003c\/li\u003e\n\u003c\/ul\u003e \u003cb\u003eWho This Book Is For\u003c\/b\u003eData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 12\/24\/2022\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9781484289778\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 174\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.61lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.41d","brand":"Akshay R. Kulkarni, Adarsha Shivananda, Anoosh Kulkarni","offers":[{"title":"Default Title","offer_id":42589539991733,"sku":"9781484289778","price":32.29,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0473\/0804\/6492\/products\/img_d298ebeb-d536-4190-96a5-d243545dd722.jpg?v=1673326667","url":"https:\/\/pastforward.org\/products\/time-series-algorithms-recipes-implement-machine-learning-and-deep-learning-techniques-with-python-9781484289778","provider":"Past Forward","version":"1.0","type":"link"}