Deepart.io Reviews

Plotly Reviews

Deepart.io mentions (18)

• Schweizerische!

  I think deepart.io was the first free style-transfer tool. Source: about 2 years ago

• AI Stylized Render of a 3D Model I made. I was told you might like it here.

  Https://deepart.io is a bit weird sometimes. But if you fiddle with the settings for a bit it's really good. Source: about 2 years ago

• The picture doesn’t do this art justice. It’s soooo perfect!!

  I wouldn't. It's clearly one of the deep learning filters slapped over a screenshot. It's low effort and anyone can make it using something like this https://deepart.io/ something done by hand would look so much better. Source: about 2 years ago

• ILPT Request: Ways to make pictures look handdrawn?

  Use an ai site like deepart.io, input the picture, and then an image of a drawing you want to recreate the style of. It basically recreates the image but in the style of the drawing. Source: over 2 years ago

• Fractured Existence, me, digital, 2021

  For those of you looking to try this out too, visit https://deepart.io/ Or Google for style transfer AI. Source: over 2 years ago

Plotly mentions (30)

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 20 days ago

• Python equivalent to power bi/power query?

  For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 7 months ago

• Junior Developer asked to make Saaas in first month.

  If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago

• Wait, but I thought they were the same thing?

  I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: over 1 year ago