At Hypriot, he helps to make the uprising Docker technology ready for the Internet of Things, i. Mathias bootstrapped a vivid Docker Community with regular meetups, where he gives talks about Docker and its eco system. In his studies, he specialized in the energy domain energy-efficiency, renewable energy , data analytics and machine learning. Privately, Mathias is very passionate about all topics related to sustainability. A major barrier for widespread use of electric cars is the high level of uncertainty that potential buyers face when it comes to estimating the car's utility for themselves. Today, the maximum driving range of an electric car is used to evaluate its utility, despite multiple studies demonstrating the limited ability of this metric to evaluate electric car utility. In addition, utility is very much influenced by an individual's driving behavior, which is not considered in the maximum driving range as utility index. Herein I identify the most significant factors for measuring utility of an electric car, and based on the results I provide a new estimate an electric car's utility. The estimation is provided for specific individual's driving behavior due to the strong influence of such behavior on car utility.
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Rather than spending a month figuring out an unsupervised machine learning problem, just label some data for a week and train a classifier. Natural Language Processing NLP is an actively developing scientific discipline engaged in the search for meaning and learning based on textual data. How can this article help you? Over the past year, the Insight team has participated in several hundred projects, combining the knowledge and experience of leading companies in the United States. They summarized the results of this work in an article, the translation of which is now in front of you, and deduced approaches to solving the most common applied problems of machine learning. We'll start with the simplest method that can work - and gradually move on to more subtle approaches like feature engineering , word vectors, and deep learning. After reading the article, you will know how to: collect, prepare, and inspect data; build simple models, and, if necessary, make the transition to deep learning; interpret and understand your models to make sure that you are interpreting information, not noise.
Nowadays working on a SRE team helping to build an awesome monitoring platform. In spare time, Eric likes to watch NHL games and learn about economics stuff. Riad Vargas is a Software Engineer at Nubank, with more than 2 years of experience developing and maintaining microservices in the financial industry, focused in functional programming, transactional databases and SRE stuff. We are going to talk about how we built, maintain and scale our microservices architecture. We are a fast-growing digital bank with a lot of challenges regarding scalability, operability and reliability and we would like to present a structured talk about the key components of our ecosystem and also how they interact with each other. Since day-one we architectured our entire infrastructure to run on cloud and to be platform agnostic, that gave us the ability of growing fast and ensuring our high standards reliability. Nowadays we decouple our infrastructure from EC2 Amazon instances to Kubernetes where we gained the desired agnosticism. There's a few characteristics that are not so usual and gives us a lot of leverage when compared to our competitors, things like Sharding and Homogeneous Codebase, using functional programming as our main paradigm. Also, we build and maintain abstractions that help our engineering team to smoothly operate and constantly improve their microservices, and furthermore the products we offer to customers. One of things we use to achieve high levels of resilience and reliability is Kubernetes with our own developed tooling and abstractions, which allows us to provide fast interaction cycle and an even more optimized way to deploy services and other infrastructure parts.
Design patterns, distributed systems, reactive programming Enterprise systems architecture Nodejs, Java,. Application performance and monitoring Prometeus, Zipkin, NewRelic, etc. Cloud computing AWS, Azure, etc. Testing automation Big Data and Machine Learning. Yaroslavl is the largest and oldest founded city on the Golden Ring, a fact underscored by its place of honour on the Russian rouble note including the domed church of John the Baptist on the back. Read more on LonelyPlanet. Menu Submit a talk Why visit?