Machine Learning Open Source

Improve machine learning algorithm accuracy with human curated data.



When performing pattern recognition or predictive analysis on large data sets, machine learning is your best option. But, while open source software and other cheaper options make it easy to implement, machine learning algorithms still struggle with accuracy.  And, let’s face it, an 80% accuracy rate just isn’t good enough. Without quality training data, machine learning algorithms can only get you so far.

CrowdFlower combines the best of machine learning with human intelligence to get you useful results. It’s now easy to collect and label training data and connect it to your machine learning algorithms. It is also easy to identify where the algorithms are struggling and retrain them through active learning. CrowdFlower also believes that open data is the new open source. We have created an open source library, Data for Everyone, that will provide more training data for your machine learning algorithms.  

Using CrowdFlower is easy.

  • Upload your data. Your data can be images, audio, video, text, or your mission-critical system of record.
  • Design and launch your job. Customize your design settings and our human-in-the-loop platform will route the tasks based on your requirements.
  • Use your results. Download your enriched data, or use machine learning and human-in-the-loop to make active learning work for you.

Get the most from your open source machine learning algorithms.  Download our whitepaper today and see what CrowdFlower can do for you!