Developing machine learning solutions that give a lift from your existing prediction algorithms is not an easy task. They require a multitude of activities to get it right including cleaning up the data, setting up the infrastructure, testing &re-testing the model & finally deploying the algorithm.
Here are five machine learning services that can help reduce the pain of deploying your machine learning solution.
Based on Microsoft’s Azure Cloud Platform, Azure Machine Learning offers a streamlined experience for all data scientist skill levels, from setting up with only a web browser, to using drag and drop gestures and simple data flow graphs to set up experiments. Machine Learning Studio features a library of time-saving sample experiments, R and Python packages and best-in-class algorithms from Microsoft businesses like Xbox and Bing. Azure ML also supports R and Python custom code, which can be dropped directly into your workspace. Experiments are easily shared, so others can pick up where you left off.
Google’ Cloud Prediction API provides pattern-matching and machine learning capabilities. Given a set of data examples to train against, you can create applications that can perform the following tasks:
The Algorithms.io cloud platform makes it easy to use machine learning algorithms to classify streaming data from connected devices. Algorithms.io’s catalog of machine learning algorithms classifies streaming data into discrete actions in real-time with up to 99% accuracy. They provide the infrastructure necessary to collect, store, and classify streaming data, all as a service.
BigML takes the complexities out of creating a high-availability, low-latency Machine Learning system created especially for your data. You will not only gain valuable insights from your data, you will most likely enjoy it. You can upload your data or connect to your cloud data (such as Google Drive or Google Cloud) via APIs, create data structured data sets from those sources, construct models and finally make predictions.
5. Ersatz Labs
Ersatz is a web-based general purpose platform for machine learning with support for GPU-based deep learning. It's geared towards aspiring and working data scientists with stuff to do. Ersatz has a number of components designed to make modern machine learning workflows much more efficient. Primarily, these include tools for data wrangling, model training, and machine learning infrastructure.
Nutonian's Data Science as a Service offering, Eureqa, enables industry leading organizations to solve their most challenging business problems. With more than 80,000 installations globally, the Robotic Data Scientist provides vertically-focused application modules for financial services, life sciences, retail, telecommunications and utilities to compute millions of potential solutions every second of every day.