Pro tip from community member Eric Strobel: "If you click & hold your mouse on a slider, you can use the arrow keys to adjust the slider value incrementally. Right & up both increment the value. Left & down both decrement the value." Thanks for the tip, Eric!
Hey. Let me ask about your computer configuration. I'm asking because when you change the values, your plots change so smoothly. In my computer, with 2.3MHz octa core, ssd and 24gb ram specs the changes suffer a huge delay. Any top to accelerate pluto notebook? Oh yeah, it's a 1050ti nvidia gpu...
@@rodolfosilva1797 2.3MHz or 2.3GHz? I'm using a Desktop PC running Windows 11. My CPU has a base clock speed of 3.7 GHz. I have 10 cores with 20 threads. RAM is 64GB. My GPU is the NVIDIA GeForce RTX 2080 Ti. I'm guessing the delay may be caused by the difference in our clock speeds. The only thing I can suggest is to try lowering the timesteps by using the "saveat" keyword argument when calling the solve() function. Here's a link to the keyword arguments that you can try with the solve() function: docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/ Good luck!
Gracias, Doggo. Gran video. Enseña de manera honesta, sin trucos, algo que escasea cada vez más. ¿Abordará las ecuaciones en diferencias (difference equations) y sistemas dinámicos? Gracias de nuevo.
¡Gracias por ser miembro del canal! Estoy planeando cubrir sistemas dinámicos simples. No estaba planeando cubrir ecuaciones de diferencia, pero lo pondré en mi lista de "cosas por hacer".
![[07x06] How to Solve Second Order ODEs in Julia using DifferentialEquations.jl and Pluto](http://i.ytimg.com/vi/Oqu_6Ve6DoU/mqdefault.jpg)
![[07x06] How to Solve Second Order ODEs in Julia using DifferentialEquations.jl and Pluto](/img/tr.png)
![[10x24] What does "Multiple Dispatch" mean in Julia?](/img/n.gif)
Pro tip from community member Eric Strobel: "If you click & hold your mouse on a slider, you can use the arrow keys to adjust the slider value incrementally. Right & up both increment the value. Left & down both decrement the value." Thanks for the tip, Eric!
Hey. Let me ask about your computer configuration. I'm asking because when you change the values, your plots change so smoothly. In my computer, with 2.3MHz octa core, ssd and 24gb ram specs the changes suffer a huge delay. Any top to accelerate pluto notebook? Oh yeah, it's a 1050ti nvidia gpu...
@@rodolfosilva1797 2.3MHz or 2.3GHz? I'm using a Desktop PC running Windows 11. My CPU has a base clock speed of 3.7 GHz. I have 10 cores with 20 threads. RAM is 64GB. My GPU is the NVIDIA GeForce RTX 2080 Ti. I'm guessing the delay may be caused by the difference in our clock speeds. The only thing I can suggest is to try lowering the timesteps by using the "saveat" keyword argument when calling the solve() function. Here's a link to the keyword arguments that you can try with the solve() function: docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/ Good luck!
@@doggodotjl OK. GHz. But now make some sense to me. Regards.
An idea, a video on Turing package in Julia. Could be really interesting given that it is about probabilistic programming.
Thank you for the suggestion! I will put it on my "to do" list!
Gracias, Doggo. Gran video. Enseña de manera honesta, sin trucos, algo que escasea cada vez más. ¿Abordará las ecuaciones en diferencias (difference equations) y sistemas dinámicos? Gracias de nuevo.
¡Gracias por ser miembro del canal! Estoy planeando cubrir sistemas dinámicos simples. No estaba planeando cubrir ecuaciones de diferencia, pero lo pondré en mi lista de "cosas por hacer".
Amazing as allways!
Thanks!
Doggo, you're AWESOME!
Thanks!