Hyperparameter tuning is a way to find the best machine learning model. We make it ridiculously easy to run hyperparameter sweeps using simple algorithms like grid search, to more modern approaches like bayesian optimization and early stopping.
Sweeps launched on Product Hunt on January 30th, 2020 and earned 87 upvotes and 19 comments, placing #15 on the daily leaderboard. Hyperparameter tuning is a way to find the best machine learning model. We make it ridiculously easy to run hyperparameter sweeps using simple algorithms like grid search, to more modern approaches like bayesian optimization and early stopping.
Sweeps was featured in Developer Tools (511.4k followers), Artificial Intelligence (466.8k followers) and Tech (622k followers) on Product Hunt. Together, these topics include over 316.7k products, making this a competitive space to launch in.
Who hunted Sweeps?
Sweeps was hunted by Lukas Biewald. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Sweeps stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Lukas Biewald