Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications, (PDF) offers a essential coaching and useful resource instrument to assist engineers perceive machine studying principle and observe, notably referencing use circumstances in oil and gasoline. The reference strikes from describing how Python works to step-by-step examples of utilization in a number of oil and gasoline situations, like effectively testing, shale reservoirs, and manufacturing optimization. Petroleum engineers are rapidly implementing machine studying strategies to their information challenges, however there may be an absence of references past the maths or heavy principle of machine studying. Machine Learning Guide for Oil and Gas Using Python particulars the open-supply instrument Python by describing the way it works at an introductory stage then linking to the way to implement the algorithms into completely different gasoline and oil situations. While associated sources are sometimes too mathematical, this ebook balances principle with functions, together with use circumstances that help remedy completely different oil and gasoline information challenges.
- Includes probably the most generally used algorithms for each supervised and unsupervised studying
- Assists readers perceive how open-supply Python can be utilized in sensible oil and gasoline challenges
- Offers a balanced strategy of each principle and practicality whereas transitioning from introductory to superior analytical strategies
NOTE: The product only contains the ebook, Machine Learning Guide for Oil and Gas Using Python in PDF. No access codes are included.
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