One of the biggest players in the eCommerce world are going through a massive data & analytics transformation, and introducing some world-class analytics techniques using cutting edge real-time/streaming tools (e.g. This is an awesome opportunity to join an exciting data innovations team - your platform will help to generate advanced commercial insight through machine learning and recommendation systems. The Data Science Engineer will likely be a Big Data Engineer with stats/analytics experience, or a Data Scientist with a Computer Science/programming background. Please register your interest by sending your CV via the Apply link on this page. If you decide this role isn't the one for you, please contact Jethro Willett at Harnham - the Big Data market has never been busier and we're working on 20 live roles
This month Google revealed a major new approach to A.I. development that seems to call out to the most sensational and apocalyptic predictions in all of science fiction. Called "AutoML" for "auto-machine learning," it allows one A.I. to become the architect of another, and direct its development without the need for input from a human engineer. On the surface, that sounds like the sort of thing that could lead to the runaway evolution of the singularity, but it's actually Google's bid to put the incredible power of machine learning in the hands of ordinary humans. In essence, AutoML's strategy of using neural networks to design other neural networks is familiar; making programs to edit the code of other programs is the definition of machine learning. What makes AutoML new is how early into the process of designing a neural net it begins to intervene; AutoML doesn't just refine simple models that already exist, but selects those models in the first place, and then refines them on its own.
With every organization digitizing its operations and taking advantage of data science tools, artificial intelligence, machine learning, the demand for professionals in their domain is always high. With machine learning being an important aspect of all automation tools, machine learning engineers are in the highest demand. According to Brandon Purell, Senior Analyst at Forrester Research, "one hundred percent of any company's future success depends on adopting machine learning. For companies to be successful in the age of the customer, they need to anticipate what customers want, and machine learning is absolutely essential for that." Let's understand why the demand for a machine learning engineer is more than ever.
The role of the machine learning engineer has changed. In the past, a machine learning engineer was a software engineer with some knowledge of machine learning concepts. Today, a machine machine learning engineer is a software engineer who not only understands the latest machine learning and deep learning concepts but is able to deploy an AI system in production that is highly reliable, fast and scalable. In this course, you'll learn how to scale up your application and deploy them into production. By the end of the course, you'll have designed an ML/DL system, built a prototype and deployed a running application that can be accessed via API or web service.