It is TIME to change the way you process -and present- your geochemical data! While there are still companies trying to discover the next gold deposit just with FA results (good luck on that!), more and more geologists are starting to work with Big Data… or at least with multi-element analysis. Some are even combining geochemical data with geophysical, structural, and other types of geological data. They are on the right path! Machine learning, or artificial intelligence, can help you process large and complex data sets. Here you will learn, step by step, how to use WEKA to process your data and to extract useful information that not only will help you locate your next target, but also will help you save money and time. However, working with multivariable data sets is tricky. One of the most commonly use methods in statistics, correlation analysis is not effective when dealing with “close data” (all geochemical data is close… more on that inside the book). So you need to use compositional data analysis to really extract useful information of your data. Finally, I will introduce you to iNZight (and a couple of his friends) as a way to present your results that go beyond the usual Excel tables and graphics. Many times, these graphics will help you find relationships that were not clear before and will help with your exploration efforts. Hope you will find this graphical guide useful and good luck processing your next data set!
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 31789462
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 31789462-n
Anzahl: Mehr als 20 verfügbar
Anbieter: California Books, Miami, FL, USA
Zustand: New. Print on Demand. Bestandsnummer des Verkäufers I-9781548620332
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 31789462
Anzahl: Mehr als 20 verfügbar
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
Paperback / softback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Bestandsnummer des Verkäufers C9781548620332
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 31789462-n
Anzahl: Mehr als 20 verfügbar
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
Paperback. Zustand: new. Paperback. It is TIME to change the way you process -and present- your geochemical data! While there are still companies trying to discover the next gold deposit just with FA results (good luck on that!), more and more geologists are starting to work with Big Data. or at least with multi-element analysis. Some are even combining geochemical data with geophysical, structural, and other types of geological data. They are on the right path! Machine learning, or artificial intelligence, can help you process large and complex data sets. Here you will learn, step by step, how to use WEKA to process your data and to extract useful information that not only will help you locate your next target, but also will help you save money and time. However, working with multivariable data sets is tricky. One of the most commonly use methods in statistics, correlation analysis is not effective when dealing with "close data" (all geochemical data is close. more on that inside the book). So you need to use compositional data analysis to really extract useful information of your data. Finally, I will introduce you to iNZight (and a couple of his friends) as a way to present your results that go beyond the usual Excel tables and graphics. Many times, these graphics will help you find relationships that were not clear before and will help with your exploration efforts. Hope you will find this graphical guide useful and good luck processing your next data set! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9781548620332
Anzahl: 1 verfügbar