I tried it with vispy outside of a jupyter notebook, and it does work. I get two windows with the expected outputs and they're independent of each other. Here's that script: #!/usr/bin/env python3 from vispy import scene from vispy.geometry.torusknot import TorusKnot import numpy as n...
Tracking: multiple 3D vispy based visualisations do not work in a single jupyter notebook #422 Open sanjayankur31 opened this issue Sep 5, 2024· 0 comments Comments Member sanjayankur31 commented Sep 5, 2024 Upstream issue filed here: vispy/jupyter_rfb#99 sanjayankur31 added the T: ...
Note that if you’re using Jupyter,you can skip this code! To set up Plotly to render your plots as svg images in your IDE, you can run the following code: import plotly.io as pio pio.renderers.default = 'svg' Once you’ve run all of this preliminary code, you should be read to...
Professionals in data science and machine learning frequently utilize multiple monitors to manage the many components of AI projects. A typical workflow for a data scientist involves writing code (in Python/R or using tools like Jupyter notebooks), examining datasets, monitoring training processes for...
I often have to to plot multiple time-series with different scale of values for comparative purposes, and although placing them in different rows are useful, placing on a same graph is still useful sometimes...I searched a bit about this, and found som..
which I implemented in the asset.paths() function. The asset.paths() function is based on theSimulating Multiple Asset Paths in MATLABcode in Matlab. asset.paths <- function(s0, mu, sigma, nsims = 10000, periods = c(0, 1) # time periods at which to simulate prices ...
(e.g., ResNet18/34/50, DenseNet, etc.) Transfer learning techniques Deliverables: -Folder-organized dataset (wheezing vs. non-wheezing) - Trained model and weightfiles- Jupyter Notebook or Python script for the entire pipeline - Evaluation report (accuracy, sensitivity, specificity, F1 score,...
In this post, we discussed how you can maximize the number of tuning jobs you can launch in parallel with SageMaker, which reduces the total time it takes to run HPO with custom user-specified objective metrics. We first discussed a Jupyter notebook based approach that can be used by in...
is based on Bayes factors calculated in the Jupyter notebookcladeAnalysis.ipynb. This notebook has a bug in the functionclade_analysis_updated. Re-running the main analysis without the bug reduces the Bayes factors by a factor of six. This significantly reduces confidence in the authors' ...
You can use Jupyter Notebook to complete the task, but we highly recommend using Google Colab instead. Do not be surprised that below is all the code you will need. This methodology uses Transformers.Transformers(formerly known as PyTorch-transformers and PyTorch-pre-trained-BERT) provide general...