CFSG Module F: Coupling Machine-Learning and geostatistical techniques using Python | Training course
Learn how to implement Machine Learning techniques in Python code for data classification.
Objectives
The CFSG (Specialized Training Cycle in Geostatistics) is a high-level training program in mining geostatistics delivered by the Geostatistics Team from Mines Paris and Geovariances. This program aims to equip you with an in-depth understanding of geostatistics for mineral resource estimation, enabling you to create block models your company needs for confident mine planning when you return to work. Throughout the training, you will learn the theoretical aspects of the techniques presented and practice them through various exercises and a real-world project.
CFSG is intended for individuals whose time zone is aligned with Europe (France) and the Americas (Brazil). It will be delivered online in 6 modules over 9 weeks throughout 2024, starting in February.
Module content
This module is the sixth and last one of the CFSG series. At the end of this course, you’ll be able to perform an initial data classification using Python and Machine Learning techniques.
THEORY
- Introduction to Machine Learning
– Use examples
– Regression and classification
– Cost functions
– Hypothesis class
– Generalization and overfitting - Linear and logistic regression, Trees
- Naîve Bayes classification
- Neural Networks, Random Forest
PRACTICE
Exercises to learn how to use Python and Machine Learning algorithms to classify data, analyze the quality of the result, and compare it to classical geostatistical techniques.
Additional modules
Each module can be attended independently of each other. However, it is important to note that completion of Module A or having experience in geostatistics and Isatis.neo is a prerequisite for participation in any of these modules.
- Module A: Geostatistics Fundamentals (mandatory)
May 13-24 & June 3-14, 2024 – 20 days
Learn the fundamentals of mining geostatistics for block modeling. - Module B: Recoverable resources with nonlinear methods (optional)
July 1-5, 2024 – 5 days
Learn how to compute recoverable resources considering mining selectivity and quantify the uncertainties. - Module C: Non-stationary geostatistics (optional)
Sept. 16-20, 2024 – 5 days
Learn how to constrain the block model with geological trends. - Module D: Facies simulations (optional)
Sept. 30 – Oct. 4, 2024 – 5 days
Learn how to achieve reliable and realistic facies modeling. - Module E: Domaining (optional)
Nov. 18-22, 2024 – 5 days
Get introduced to a powerful machine-learning-based technique for geological domaining.
Outlines
- Half of the training program is devoted to methodological presentations, the other half to practical exercises to deepen the understanding of concepts.
– The methodological courses are given by Mines Paris professors.
– Geovariances consultants will drive the practical sessions from our French office.
– For more convenience, these courses are recorded and made available to participants during the session and until one month after the end of the course.
- A typical training week would then be:
– Monday, Tuesday, Wednesday, and Thursday: theoretical course (on a half-day) and hands-on practice with Isatis.neo Mining Edition (on the half-day following the theoretical course).
– Friday: homework using Isatis.neo Mining Edition with compulsory rendering at the end of the day. Live corrections and comments from the teaching team. Validation of prior learning. - CFSG is a full-time training. You are required to be present/connected for the duration of the sessions.
- CFSG is a certification training. The knowledge acquired in each module is validated through an examination. At the end of each module, you will get a training certificate that officially recognizes the full completion of the module.
- Course material and a temporary software license are provided.
- A minimum number of 8 participants is required for a module actually to take place.
Who should attend
The CFSG training program is meant for mining geologists and engineers willing to achieve a high level of geostatistics and boost their careers.
Module A is ideal for newcomers to mining geostatistics. Modules B and F are designed for individuals who wish to delve into more advanced geostatistics.
Prerequisites
The course is delivered in English and requires a good level of this language. Sound notions of mathematics are also recommended.
As the course is online, a good quality internet connection is required. We also appreciate that the participant’s camera is turned on for the session.
Benefit from the trainers’ high expertise in geostatistics
From Mines Paris – PSL
From Geovariances