Author: Sara Forte
Publisher: Ten Speed Press
ISBN: 1607741156
Category : Cooking
Languages : en
Pages : 254
Book Description
Sprouted Kitchen food blogger Sara Forte showcases 100 tempting recipes that take advantage of fresh produce, whole grains, lean proteins, and natural sweeteners—with vivid flavors and seasonal simplicity at the forefront. Sara Forte is a food-loving, wellness-craving veggie enthusiast who relishes sharing a wholesome meal with friends and family. The Sprouted Kitchen features 100 of her most mouthwatering recipes. Richly illustrated by her photographer husband, Hugh Forte, this bright, vivid book celebrates the simple beauty of seasonal foods with original recipes—plus a few favorites from her popular Sprouted Kitchen food blog tossed in for good measure. The collection features tasty snacks on the go like Granola Protein Bars, gluten-free brunch options like Cornmeal Cakes with Cherry Compote, dinner party dishes like Seared Scallops on Black Quinoa with Pomegranate Gastrique, “meaty” vegetarian meals like Beer Bean– and Cotija-Stuffed Poblanos, and sweet treats like Cocoa Hazelnut Cupcakes. From breakfast to dinner, snack time to happy hour, The Sprouted Kitchen will help you sneak a bit of delicious indulgence in among the vegetables.
The Sprouted Kitchen
Machine Learning for Time Series Forecasting with Python
Author: Francesca Lazzeri
Publisher: John Wiley & Sons
ISBN: 1119682371
Category : Computers
Languages : en
Pages : 224
Book Description
Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models’ performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.
Publisher: John Wiley & Sons
ISBN: 1119682371
Category : Computers
Languages : en
Pages : 224
Book Description
Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models’ performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.
Transactions on Rough Sets XXIII
Author: James F. Peters
Publisher: Springer Nature
ISBN: 3662665441
Category : Computers
Languages : en
Pages : 513
Book Description
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXIII in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.
Publisher: Springer Nature
ISBN: 3662665441
Category : Computers
Languages : en
Pages : 513
Book Description
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXIII in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.
Cmt Curriculum Level I 2023
Author: Cmt Association
Publisher: John Wiley & Sons
ISBN: 1394184778
Category :
Languages : en
Pages : 675
Book Description
Get Your Copy of the 2023 Official CMT(R) Level I Curriculum As the authoritative introduction to the basics of technical analysis, the Official CMT(R) Level I Curriculum includes the tools, content, and terminology you will need to prepare for the Level I exam and beyond. Published in partnership with the CMT Association, CMT Curriculum Level I 2023: An Introduction to Technical Analysis explores theory and history, markets, market indicators, construction, confirmation, cycles, selection and decision, system testing, and statistical analysis. This text covers all concepts appearing on the Level I CMT(R) exam, featuring industry-relevant topics and treatments of technical analysis in the context of portfolio management.
Publisher: John Wiley & Sons
ISBN: 1394184778
Category :
Languages : en
Pages : 675
Book Description
Get Your Copy of the 2023 Official CMT(R) Level I Curriculum As the authoritative introduction to the basics of technical analysis, the Official CMT(R) Level I Curriculum includes the tools, content, and terminology you will need to prepare for the Level I exam and beyond. Published in partnership with the CMT Association, CMT Curriculum Level I 2023: An Introduction to Technical Analysis explores theory and history, markets, market indicators, construction, confirmation, cycles, selection and decision, system testing, and statistical analysis. This text covers all concepts appearing on the Level I CMT(R) exam, featuring industry-relevant topics and treatments of technical analysis in the context of portfolio management.
The National Poland-China Record
Author: National Poland-China Record Company
Publisher:
ISBN:
Category : Poland-China swine
Languages : en
Pages : 1184
Book Description
Publisher:
ISBN:
Category : Poland-China swine
Languages : en
Pages : 1184
Book Description
Practical Time Series Analysis
Author: Aileen Nielsen
Publisher: "O'Reilly Media, Inc."
ISBN: 1492041602
Category : Computers
Languages : en
Pages : 504
Book Description
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
Publisher: "O'Reilly Media, Inc."
ISBN: 1492041602
Category : Computers
Languages : en
Pages : 504
Book Description
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
The American Shorthorn Herd Book
American Herd Book
Author: American Short-horn Breeders' Association
Publisher:
ISBN:
Category : Cattle
Languages : en
Pages : 1218
Book Description
Publisher:
ISBN:
Category : Cattle
Languages : en
Pages : 1218
Book Description
The Catalog of Information Sources for the City of Los Angeles: pt. 1. The catalog: data dictionary
Author: Los Angeles (Calif.). Community Analysis Bureau
Publisher:
ISBN:
Category : Los Angeles (Calif.)
Languages : en
Pages : 216
Book Description
Publisher:
ISBN:
Category : Los Angeles (Calif.)
Languages : en
Pages : 216
Book Description
Marine Engineers' Handbook
Author: Frank Ward Sterling
Publisher:
ISBN:
Category : Marine engineering
Languages : en
Pages : 1518
Book Description
Publisher:
ISBN:
Category : Marine engineering
Languages : en
Pages : 1518
Book Description