Random Forest Machine Learning Tutorial in Python for Lithology Prediction - Includes Overview

preview_player
Показать описание
Random forest is a very popular machine learning algorithm that can be used for both classification and regression. Within this tutorial we will go over the basics of the random forest algorithm before moving onto a real world example where we are attempting to predict a lithological class from well log measurements.

Data Source

▼ ---- SUPPORT THE CHANNEL ---- ▼

▼ ---- GET THE CODE --- ▼

▼ ---- RECOMMENDED BOOKS ---- ▼
As an Amazon Associate I earn from qualifying purchases. By buying through any of the links below I will earn commission at no extra cost to you.

PYTHON FOR DATA ANALYSIS: Data Wrangling with Pandas, NumPy, and IPython

FUNDAMENTALS OF PETROPHYSICS

PETROPHYSICS: Theory and Practice of Measuring Reservoir Rock and Fluid Transport Properties

WELL LOGGING FOR EARTH SCIENTISTS

GEOLOGICAL INTERPRETATION OF WELL LOGS

▼ ---- SOCIAL CHANNELS ---- ▼
Thanks for watching, if you want to connect you can find me at the links below:

Be sure to sign up for my newsletter to be kept updated when I post and share new content on YouTube and Medium.

#datascience #petrophysics #python #machinelearning #geosciences
Рекомендации по теме
Комментарии
Автор

As an IT Student looking forward to learning Data Science specifically Machine Learning, this is a great way to learn how to sort the data; clean it, verify its accuracy and present it.
Ever since my university presented Machine Learning, I've been hooked ever since.

I'm looking forward to watching more of your videos, please do keep uploading!

giopremiro
Автор

Thanks for being a great teacher, Andy. Please can you do a video on Artificial neural networks in machine learning?

faicornelius
Автор

Can you please send me the prediction of astroid orbit path using random forest algorithm project video

ravinayak
Автор

Hello Andy thanks for your excellent channel, I am trying to use this workflow for predicting facies, those faces exhibit a significant imbalance in the distribution, I mean some of them only have a few quantities, but others have extremely high amounts, so using train_test_split could no ensure to cover those facies with low presence, so could you please explain to us how to deal with this problem, I was reading about (StratifiedKFold, KFold) but I am no sure how to use it.

Jean-tfgh
Автор

Hi there! Great channel! I loved this video, but I have a question: once we have a model and we have found that it is quite accurate (in your video 91%), is it possibile to put as input a row of values (our X) to make a prediction (y) of the specific rock? My idea is the following one: I have a new input line appending to my df, can I predict its y value (thus, the rock)? How can I do that? In a very basic form it should be something like this: Thanks!

tommasoseneca
Автор

HI Andy thanks for the great work you are doing
I am learning a lot from you .
can you please check the link for the code in this video it seems it is the wrong one as it took me to the earthquake code

faisalkhalifa
Автор

hello! how to convert las files to csv in a proper way? any tutorials for that theme?

trolololo
Автор

This guy talks way too fast and isn't clear. He may be brilliant, but i don't think he should be an educator.

johnspivack
welcome to shbcf.ru