Dask vs. IntelliHub vs. Python vs. hug Comparison Chart

We work closely with businesses to find out what are the common issues preventing companies from realising benefits. We design to open up opportunities that were previously not viable using conventional approaches Corporations -big and small, require an AI platform with complete empowerment and ownership. Tackle data privacy and adopt to AI platforms at a sustainable cost. Enhance the efficiency of businesses and augment the work humans do. We apply AI to gain control over repetitive or dangerous tasks and bypass human intervention, thereby expediting tasks with creativity and empathy. Machine Learning helps to give predictive capabilities to applications with ease. You can build classification and regression models. It can also do clustering and visualize different clusters. It supports multiple ML libraries like Weka, Scikit-Learn, H2O and Tensorflow. It includes around 22 different algorithms for building classification, regression and clustering models.

Drastically simplify API development over multiple interfaces. With hug, design and develop your API once, then expose it however your clients need to consume it. Be it locally, over HTTP, or through the command line - hug is the fastest and most modern way to create APIs on Python3. hug has been built from the ground up with performance in mind. It is built to consume resources only when necessary and is then compiled with Cython to achieve amazing performance. As a result, hug consistently benchmarks as one of the fastest Python frameworks and without question takes the crown as the fastest high-level framework for Python 3. hug makes it easy to expose multiple versions of your API. With hug you can simply specify what version or range of versions an endpoint supports and then automatically have that enforced and communicated to your API's users.