Mohammed Abu El Majd's repositories
geophysical_notes
Collection of geophysical notes in the form of IPython/Jupyter notebooks.
awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
Data-Science-ML-Full-Stack-2022
Everything you need to know for data science.
data-science-road-map
A roadmap for those looking to start or expand a career in the data community
Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
example-ml-project
Deploying Model to Production with FastAPI Docker
Jupyter-Notebooks_for-Characterization-of-a-New-Open-Source-Carbonate-Reservoir-Benchmarking-Case-St
We have used the new hierarchical carbonate reservoir benchmarking case study created by Costa Gomes J, Geiger S, Arnold D to be used for reservoir characterization, uncertainty quantification and history matching.
las
Python reader for Canadian Well Logging Society LAS (Log ASCII Standard) files.
lightweight-charts
Financial lightweight charts built with HTML5 canvas
Machine-Learning-Competition-2023
The 3rd SPWLA ML competition
Machine-Learning-Deep-Learning
This repository has all my projects on Oil and Gas (and Non Oil & Gas) Machine Learning Topics
Machine-Learning-Engineer
Machine Learning Engineer Roadmap
machine-learning-zoomcamp
Learn ML engineering for free in 4 months!
pandas-profiling
Create HTML profiling reports from pandas DataFrame objects
Petrophysical-Well-Logs-from-several-wells
Introduction to Dataset:¶ This dataset consists of petrophysical well logs from several wells. This is a relational dataset. You need to prepare data step by step as mentioned below and try to extract some insights and valuable information. DEPTH_MD: This column is measured depth in meter. (Continuous data) WELL: Well name (Categorical data) X_LOC: Geographical X location in UTM system. (Continuous data) Y_LOC: Geographical Y location in UTM system. (Continuous data) GROUP: The interval of rocks that can include several FORMATION (Categorical data) FORMATION: The interval of rocks that has geological special meaning (Categorical data) DTC: This log is a measurement of acoustic wave in rocks inside oil and gas well (Continuous data) PEF: This is photoelectric log helping to recognize lithology (Continuous data) NPHI: This is a Neutron log for porosity evaluation. (Continuous data) RHOB: This is rock medium density measurements(Continuous data) lithology_name: type of the rocks (Categorical data)
Practical-Time-Series-In-Python
Practical guidance for time series analysis in Python
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Python
All Algorithms implemented in Python
saas_trial_one
#https://saasitive.com/tutorial/django-react-boilerplate-saas/
seismic-deeplearning
Deep Learning for Seismic Imaging and Interpretation
View-Thin-Section-Images-from-a-Porosity-Permeability-Cross-Plot-using-Python-Altair
This is some very simple python code to view thin sections from a porosity vs. permeability cross plot using python's Altair and Pane
volve-machine-learning
Exploration of machine learning in the Volve field dataset