"The AI market is expected to hit the half a trillion dollar mark in a few years and Snorkel AI is solving one of the biggest problems in AI-the data."
"The biggest challenge we have—which is true of any AI/ML project, but is especially so in clinical contexts—is how do we label [training] data? Our labelers are physicians and researchers, their time is very expensive.”
Aquarium Learning helps deep learning teams improve their model performance by improving their datasets. Aquarium Learning wants to give everyone the same world-class ML tooling that big companies already have access to. They want to enable domain experts to build and deploy models without specialized ML expertise, making it easier to build and improve real-world ML products.
Neptune.ai is an experiment tracking hub bringing organization and collaboration to data science projects. Neptune records your entire experimentation process - exploratory notebooks, model training runs, code, hyperparameters, metrics, data versions, results, exploration visualizations, and more. Everything is stored and backed-up in an organized knowledge repository, ready to be accessed, analyzed, shared, and discussed with your team. No matter what type of problems you are working on, Neptune fits them all, from evaluating credit risk to finding the nuclei in divergent images.
iMerit is working with customers to enrich and label their data and to achieve the best results from their algorithms. All the work powers advanced algorithms in machine learning, computer vision, natural language understanding, e-commerce, augmented reality, and data analytics. They work on data for transformative technologies such as advancing cancer cell research, optimizing crop yields, and training driverless cars to understand their environment.