Kaggle
Colaboratory
Driven Data
Numerai
HackerRank
DataSource.ai
Infosec Skills
DataHack & DSAT
Diff Anything
Beyond Compare
Diff Anything chooses a comparison engine that understands the inputs. Text uses a focused side-by-side diff, JSON and other structured formats compare semantic paths, CSV can match rows by key, folders recurse with ignore rules, and images add pixel heatmaps, overlay, and blink views. Compared files never leave the computer. There are no accounts, cloud comparison services, analytics, or telemetry. CLI and Git difftool modes make the same comparison model available in scripts and source-control workflows.
Kaggle
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Diff Anything's answer:
Diff Anything is a local-first desktop comparison and merge application that selects a comparison model for the inputs. It supports focused text diffs, semantic paths for JSON and other structured formats, key-based CSV matching, recursive folder comparison with ignore rules, and image heatmap, overlay, and blink views. Compared files stay on the computer, with no account, cloud comparison service, analytics, or telemetry.
Diff Anything's answer:
Diff Anything is a fit when you need one private desktop workflow for mixed artifacts rather than only plain text. It can compare text, structured data, CSV, folders, archives, documents, API schemas, HTTP responses, images, and binaries locally. CLI and Git difftool modes also make the same comparison model available in scripts and source-control workflows.
Diff Anything's answer:
Diff Anything is primarily for developers comparing mixed release artifacts, teams reviewing configuration or API changes, and people who need to inspect sensitive local files without uploading their content or creating an account.
Based on our record, Kaggle seems to be more popular. It has been mentiond 103 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.
A good example: the results we published are one-shot success rates with no retries and no manual intervention. But we did re-run some failed tasks afterward. Take Task #197 on kaggle.com ("Identify the ongoing competition that offers the highest prize and find the code that received the most votes in that competition"). In our benchmark submission, it failed on an anti-bot block. On a subsequent run, TinyFish... - Source: dev.to / 3 months ago
The key to mastering data analysis is practice. Kaggle.com and World Bank provide hands-on experience with real-world data, helping you consolidate your learning and apply your skills. Trying small projects like: Analyzing Netflix ratings, Visualizing COVID-19 data and Cleaning messy sales data in Excel can help strengthen your skill. - Source: dev.to / about 1 year ago
Before you even build a model, you are going to need some kind of dataset. Usually a CSV or JSON file. You can build your own dataset from scratch using your own data, scrape data from somewhere, or use Kaggle. - Source: dev.to / over 1 year ago
Kaggle: For data science and machine learning competitions. - Source: dev.to / about 2 years ago
Need help with last minute python project (due today). Project involves choosing a dataset from kaggle.com to analyze and creating questions to answer through analyzing the data. I have a pdf file of the project guidelines if you want more details. Also on a budget. Source: about 3 years ago
Colaboratory - Free Jupyter notebook environment in the cloud.
Beyond Compare - Beyond Compare allows you to compare files and folders.
Driven Data - DrivenData hosts data science competitions to build a better world, bringing cutting-edge predictive models to organizations tackling the world's toughest problems.
Numerai - Hedge fund that crowdsources market trading from AI programmers over the Internet
HackerRank - HackerRank is a platform that allows companies to conduct interviews remotely to hire developers and for technical assessment purposes.
DataSource.ai - Community-funded data science tournaments