Häftad · Unknown · 630 sidor
- Format
- Häftad
- Språk
- Unknown
- Omfång
- 630 sidor
- Förlag
- Unknown
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and optimizing your models Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book DescriptionTime 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.
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and optimizing your models Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book DescriptionTime 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.
Priser & butiker
Priser & butiker
1 butik · Häftad · lägsta pris först
Skriver du om boken på en blogg eller sajt? .
- Frakt
- Frakt från 35 kr · fri frakt över 249 kr
- Leverans
- 2-3 vardagar. Levereras hem eller till ombud. Skickas med Schenker eller Early Bird.
- Betalning
- Kort · Swish · Faktura 30 dagar · Delbetalning · Direktbank
- Öppet köp
- 30 dagars öppet köp
- Omdöme
- 3.8 av 5 på Trustpilot (10 194 omdömen)
- Frakt
- Frakt från 35 kr · fri frakt över 249 kr
- Leverans
- 2-3 vardagar. Levereras hem eller till ombud. Skickas med Schenker eller Early Bird.
- Betalning
- Kort · Swish · Faktura 30 dagar · Delbetalning · Direktbank
- Öppet köp
- 30 dagars öppet köp
- Omdöme
- 3.8 av 5 på Trustpilot (10 194 omdömen)
Samma ISBN jämförs hos alla butiker — priserna gäller samma utgåva.
Annonslänkar: Booki kan få provision när du handlar via våra länkar. Det påverkar inte ditt pris. Externa länkar utan pris ingår inte i jämförelsen.
Annonslänkar: Booki kan få provision när du handlar via våra länkar. Det påverkar inte ditt pris. Externa länkar utan pris ingår inte i jämförelsen.
Håll koll på priset
Håll koll på priset
Väntar du på ett lägre pris?
Bevaka priset på denna utgåva av Time Series Analysis with Python Cookbook och få besked när det sjunker.
Spara den här boken
Logga in för att lägga till i din bokhylla, bevaka priset och recensera.
Om boken
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and optimizing your models Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book DescriptionTime 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.
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and optimizing your models Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book DescriptionTime 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.
Bokfakta
Författare
Packt Publishing Limited
Format
Häftad
Sidantal
630
ISBN
9781801075541
