homemade-machine-learning VS CFDPython

Compare homemade-machine-learning vs CFDPython and see what are their differences.


🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained (by trekhleb)


A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/ (by barbagroup)
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homemade-machine-learning CFDPython
7 11
22,580 3,229
- 1.4%
1.0 0.0
7 days ago 2 months ago
Jupyter Notebook Jupyter Notebook
MIT License GNU General Public License v3.0 or later
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Posts with mentions or reviews of homemade-machine-learning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-14.


Posts with mentions or reviews of CFDPython. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-03.
  • Getting started with OpenFoam and Code Contributions
    1 project | /r/CFD | 13 Jun 2023
    Is 12 steps to Navier Stokes a good start? I have done all the modules, wrote all the code by myself (except for the plotting part which I had literally no experience in) and I am trying to solve some random problems in the J P Holman heat transfer book. Then I am thinking of going through the Application part of Anderson CFD.
  • Which one is best for numerical simulations for fluid mechanics [mostly linear terms].
    3 projects | /r/CFD | 3 May 2023
  • Five-point stencil in Python for calculating 2D Laplacian
    1 project | /r/ScientificComputing | 2 May 2023
    Thank you for posting the most in-depth reply I have ever received on Reddit. This is some very good advice. I'm constantly trying to get a better understanding of solving differential equations; consequently, I'm currently solving the Gray-Scott diffusion model. My example above is based on what I've done for the Gray-Scott model. Since you seem to have experience in this area, do you have any books that you recommend for learning more about writing code to solve differential equations using finite differences, finite element, or finite volume methods? I have some books that talk about the theory but haven't found anything that gives good code examples related to the math. CFD Python has been a great resource but it doesn't provide the depth that a book would give.
  • CFD and Numerical Methods Code Projects/Assignments
    1 project | /r/CFD | 21 Jul 2022
    updated link
  • Lid driven Cavity flow - Step 11 of Prof. Lorena Barba 's CFD - python module
    1 project | /r/CFD | 25 Apr 2022
    CFDPython/14_Step_11.ipynb at master · barbagroup/CFDPython (github.com)
  • Want to move on from Fluent to actually learning CFD.
    1 project | /r/CFD | 30 Dec 2021
    This course is freely available and gives a very good hands on introduction to incompressible CFD solvers: https://github.com/barbagroup/CFDPython
  • Your MBTI type and current obsession?
    1 project | /r/mbti | 27 Dec 2021
    For CFD, I just starred looking into it recently and trying to avoid paying premium for the software and came across this recently. https://github.com/barbagroup/CFDPython
  • Poisson's Equation is the most powerful tool not yet in your toolbox
    3 projects | news.ycombinator.com | 6 Jul 2021
    There are many different ways to do what you'd like. The easiest starting point would probably be this tutorial: https://github.com/barbagroup/CFDPython

    But that won't handle turbulence. The real "turbulence problem" is that computing actual turbulent flows requires enormous computational resources. So instead of solving the Navier-Stokes equations, related equations with lower computational cost are solved. Because of how these equations are developed, they require modeling of "unclosed" terms, and this is a likely source of inaccuracy.

    If you want something relatively simple, you could take the RANS approach and use the Spalart-Allmaras model:



  • Hello guys ! I am new to learning CFD (currently in 2nd year of my undergraduate program). I am thinking of doing it all by myself. Can anybody suggest me where to start and it what order should I proceed.
    1 project | /r/CFD | 15 Apr 2021
    12 Steps to Navier Stokes by Lorena Barba link
  • Complexity Explained
    2 projects | news.ycombinator.com | 6 Feb 2021
    I sniff an air of condescension; what’s your goals therein? Are you posturing your ‘maths’ knowledge?

    I thought I was explicit in my criticism of “notation only” explanations, but perhaps a positive example would be more explicit.


    This repo explains computational fluid dynamics (an example of a complex system!) from “what is a python function” to “2d Navier stokes”.

    It shows the work of how to discretize ‘latex beautified’ notation, shows the relationship between the computations and the notation, and even explains when their LaTex strays from “conventional use of notation” and why.

    The authors even throw in traditional handwritten board lecture videos if that helps you learn better.

    complexityexplained reads like it’s written by the Spider-Man points at Spider-Man meme.

What are some alternatives?

When comparing homemade-machine-learning and CFDPython you can also consider the following projects:

lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)

AeroPython - Classical Aerodynamics of potential flow using Python and Jupyter Notebooks

wordle-solver - For educational purposes, a simple script that assists in solving the word game Wordle.

AeroSandbox - Aircraft design optimization made fast through modern automatic differentiation. Composable analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features

Nalu - Nalu: a generalized unstructured massively parallel low Mach flow code designed to support a variety of open applications of interest built on the Sierra Toolkit and Trilinos solver Tpetra solver stack. The open source BSD, clause 3 license model has been chosen for the code base. See LICENSE for more information.

rmi - A learned index structure

Flow - Flow is a sparse grid-based fluid simulation library for real-time applications.

PythonRobotics - Python sample codes for robotics algorithms.

poisson-canvas - Explore poisson equation with HTML canvas

the-elements-of-statistical-learning - My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman