Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
Based on our record, Plotly should be more popular than Numerai. It has been mentiond 33 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / 3 months ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / 5 months ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 7 months ago
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 / about 1 year ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
Numerai? Though I'm not so sure - their coin seems to have lost a lot of dollar value since I last checked. https://numer.ai/. - Source: Hacker News / about 1 month ago
For example the Numerai hedge fund's data science tournament for crowdsourced stock market prediction is giving out their expensive hedge fund quality data to their users but it's transformed enough that the users don't actually know what the data is, yet the machine learning models are still working on it. To my knowledge it's not homomorphic encryption because that would be still too computational expensive, but... - Source: Hacker News / over 1 year ago
If you are interested in the machine learning part, you can try the Numerai tournament ( http://numer.ai ). They provide obfuscated high quality hedge fund data that participants can train their models on and send back only their predictions and then they combine the user's predictions into their market neutral meta model which they actively trade. So far their fund's returns looks promising in their category... - Source: Hacker News / over 2 years ago
This does not solve your problem, but you would be interested in https://numer.ai which is a "wisdom of the crowds" ML competition for stock market predictions. Source: almost 3 years ago
Company: Numerai (https://numer.ai) Position: Web Developer Location: San Francisco (Remote/On-site with WFH days) Numerai is a new kind of hedge fund powered by thousands of competing data scientists from around the world, all working to predict the stock market. - Source: Hacker News / over 3 years ago
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Colaboratory - Free Jupyter notebook environment in the cloud.
Chart.js - Easy, object oriented client side graphs for designers and developers.
Kaggle - Kaggle offers innovative business results and solutions to companies.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Explorium - Explorium is an External Data Platform that offers ML and AI-based datasets so data scientists can take part in data science competitors and marathons to win prizes.