Subplots in #Matplotlib
Some examples using:
1️⃣ subplot_mosaic
2️⃣ subplot2grid

GitHub

Mastering #Python
Credit: Mousa

Notion is a popular tool that offers a wide range of features for note-taking, task management, document creation, and knowledge management. It provides a versatile and customizable interface that can be tailored to individual needs and workflows.

It is also available on Web, Mac, Linux, Windows, IOS and Android.

https://www.notion.so/

YouTube

Diffrax is a JAX-based library providing numerical differential equation solvers.

Features include:

1️⃣ ODE/SDE/CDE (ordinary/stochastic/controlled) solvers;
2️⃣ lots of different solvers (including Tsit5, Dopri8, symplectic solvers, implicit solvers);
3️⃣ vmappable everything (including the region of integration);
4️⃣ using a PyTree as the state;
5️⃣ dense solutions;
6️⃣ multiple adjoint methods for backpropagation;
7️⃣support for neural differential equations.

#jax
Documentation

Skorch: The Power of PyTorch Combined with The Elegance of Sklearn

Skorch immensely simplifies training neural networks with PyTorch.

Documentation

A freely available short course on neuroscience for people with a machine learning background. Designed by Dan Goodman and Marcus Ghosh.

Link

NVTOP stands for Neat Videocard TOP, a (h)top like task monitor for AMD, Intel and NVIDIA GPUs. It can handle multiple GPUs and print information about them in a htop-familiar way.

sudo apt install nvtop
GitHub

polymorphism in Python

Generative AI course for Everyone, is now available!

Learn how Generative AI works, how to use it in professional or personal settings, and how it will affect jobs, businesses and society. This course is accessible to everyone, and assumes no prior coding or AI experience.

Please access it here.

CodiumAI vscode extension provide unittest and pytest tests automatically.
It can also provide customized test by interactive chat!

Polars is a highly performant DataFrame library for manipulating structured data. The core is written in Rust, but the library is also available in Python. Its key features are:

- Fast: Polars is written from the ground up;
- I/O: First class support for all common data storage layers: local, cloud storage & databases;
- Easy to use;
- Out of Core: Polars supports out of core data transformation with its streaming API; - Parallel;
- Vectorized Query Engine;
https://pola-rs.github.io/polars/

NVIDIA just made Pandas 150x faster with zero code changes.

All you have to do is:

%load_ext cudf.pandas
import pandas as pd

Their RAPIDS library will automatically know if you're running on GPU or CPU and speed up your processing.

You can try it here

Credit: Lior

Public datasets!

Github

Why I didn't use this before?!
You can run script (also notebook) on remote server and see the results instantly, forget about repeated ssh, scp, sftp, ...

https://code.visualstudio.com/docs/remote/ssh

Understanding Deep Learning
Just took a look for now, seems 👍.

p2j - Python-to-Jupyter parser with zero intervention
The purpose of this package is to be able to run a code on Jupyter notebook without having to copy each paragraph of the code into every cell. It's also useful if we want to run our code in Google Colab. This parser isn't perfect, but you would be satisfactorily pleased with what you get.

$ pip install p2j
$ p2j script.py
$ Notebook script.ipynb written.

There are various data viewer tools for vscode, I like this one:
Data Preview
which allow to view the data in a nice table, also provide some quick visualization panels.

About 48 hours left to apply for Computational Neuroscience training program (January 22 to February 9, 2024) as a student!

Apply here by 23:59 Sunday December 17th anywhere on earth:
https://academy.neuromatch.io/pilot

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