Traveling Salesman is one of the classic NP-Hard problems: finding the optimal solution can take a long time, but there are some great shortcuts available which come close! Algorithmia now brings you a fast, near-optimal way to find the fastest route through multiple cities, thanks to the power of Genetic Algorithms and easily-accessible APIs. Read More…
Great algorithm descriptions really help developers to understand your algorithms, and help them become successful quickly. Today, we’re happy to announce that we’ve shipped several improvements aimed at helping you write great descriptions, with ready-to-edit sections aimed at helping developers quickly comprehend your algorithm’s purpose and usage.
Algorithm descriptions are based on Markdown and we’ve now shipped a Markdown editor that will let you easily edit your descriptions. The editor is based on CommonMark standard and also includes support for GFM tables.
We have a lot of fun, heavy-hitting algorithms in our marketplace: deep-learning tools like Image Tagger and pipelining mechanisms such as Video Metadata Extraction are designed to bring the power of Machine Learning to your app via easy-to-use APIs.
But sometimes, all you need to do is extract some simple information from publicly available sources: for example, finding all the email addresses of a company’s C-Suite, or summarizing the topic pages of a FAQ. You could accomplish some of it with a Python script and some RegEx magic, but that wouldn’t bring the benefits of a remote API: datacenter-grade network connections, multiple IPs, and distributed parallel processing. And it wouldn’t give you access to more complex algos such as automatic tagging or sentiment analysis. With Algorithmia, you get all the benefits of the cloud without having to build and host your own workers, plus the combined experience of our growing network of experienced algorithm developers. Read More…
Recently I gave a talk at PyData Seattle about how to ramp up your data science skills by borrowing tips and tricks from the developer community. These suggestions will help you become a more proficient data scientist who is loved by your team members and stakeholders.
This post is broken up into five parts including:
- History and controversy of the 10x developer.
- Project design.
- Code design.
- Tools for the job.
- Productionizing model.