Here's every Data Science product that launched in 2022 with enough traction to make our index. 15 total, sorted by community engagement.
15 Data Science products launched in 2022, ranked by community engagement.
Here's every Data Science product that launched in 2022 with enough traction to make our index. 15 total, sorted by community engagement.
TweetFeast is a simple utility you can use to download Twitter data. You sign in with Twitter and then you can download follower/following lists, tweets, likes, and mentions. You don't need to fiddle with API keys or write any code. Just get the data you need.
Continual is the easiest way to build continually improving predictive models - from customer churn to inventory forecasts - directly on your cloud data warehouse.
NannyML estimates real-world model performance (without access to targets) and alerts you when and why it changed. The performance estimation algorithm, confidence-based performance estimation (CBPE), was researched by core contributors.
Today’s data stack was built for yesterday’s software engineers. Data scientists deserve their own tools. Magniv is an open-source Python library that lets data scientists deploy apps independently, without relying on support from software engineers.
With this beginner-friendly CLI tool, you can create containerized machine learning models from your labeled texts in minutes. You can easily create a natural language classifier and pack it up in ready to use containers!
Gather, edit and share all your tracking plans in one place and compare them to actual data in production
Build, train and track all of your machine learning project metadata including ML models and datasets with semantic versioning, extensive artifact logging and dynamic reporting with local↔cloud training.
Obviously AI’s Data Validator runs over 1,000+ unique statistical checks on your data, then recommends fixes to make it ready for AI.
Kanjo personalises family mental health, turning children’s games and activities into accurate, evidence-based insights, advice and early detection for parents through digital biomarkers.
Extract in-demand skills from any text using the power of Skill Suggestion AI, trained by +1M online content. Easily extract skills from job postings, resumes, syllabi; automatically curate content and organize libraries using the Ultimate Skill Extractor.
CoinScreener offers accurate real-time data on the crypto market and the signal generated by AI. The insights with powerful technical analysis tools help traders get opportunities to maximize their profit.
📈 Discover early momentum signals 🎯 Track influencers' NFT & crypto picks daily 📬 Discover upcoming crypto & NFT projects 🔎 Keep tabs on crypto & NFT experts 💰 Follow leading investor profiles 📱🖥 Designed to use both on desktop and mobile
Dewey is a better way to access academic research data! We handle all the data sourcing, licensing, and provisioning, so you can focus on doing great research. Dewey unlocks private datasets for academic researchers, improving research pipelines.
Grab a CSV, upload it, and start exploring your data. Make graphs and analyze data without writing code.
Luminal is a new kind of Python notebook that makes it faster and easier to write Python scripts. Use no-code cells for common operations, and fill in the gaps with your own code. Easily share and collaborate on scripts in real-time, Google Docs style.
The category grew by 1400% compared to 2021, moving from 1 launches to 15. Average interest score across all 2022 launches: 97. Average engagement ratio: 0.28.
Use the year navigation at the top of each category page. The trends page for each category also shows top products by year in a single view.
Engagement ratio captures discussion quality. A product can game interest with a well-timed launch. It can't fake 200 substantive discussion threads. We default to engagement ratio because it's harder to inflate.
Highest community engagement at launch, measured by interest score and engagement ratio. These are traction rankings, not editorial picks.
Launch timing matters. Q1 products face different competition than Q4 products. Seasonal patterns affect both launch volume and community attention. Quarterly grouping makes comparisons fairer.
No. Some of the best-loved tools in our index have modest interest scores but sky-high engagement ratios. That pattern means a smaller audience cared deeply. I'd take that over 5,000 interest and crickets in the discussion threads.