For decades, humankind is trying to understand how the human brain functions, perceives, and reacts to the world. Artificial Intelligence (AI) attempts to understand that and build entities that can mimic human brains. There are different Definitions available on different mediums for this ultimate "Buzz word" of 21st century. And many more keeps surfacing as time passes by and as the technology evolves. However seeds of this conversations were sowed in Alan Turing's work "Computing Machinery and Intelligence" in 1950.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on talented senior Data Scientists to help us develop and improve the ETA and Routing models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a fundamental area of investment for DoorDash, ETA/Routing has among the coolest problems to solve at scale and creates a major impact on the company and its businesses. We are looking for Machine Learning Scientists, Economists, Physicists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines. You can read more about the types of Data Scientists we are looking for in our blog post Wanted: Data Scientists with Technical Brilliance AND Business Sense.

At The Data Shed, we've been working with some truly inspiring clients on anything from real-time data integration and data mining to analytics-ready data modelling and insight elicitation with data exploration and Machine Learning. The Data Shed is also offering a solution for business-wide Single View of Customer systems as a SaaS product. We face new and exciting challenges every day, from ensuring high availability and performance of critical government systems, to understanding and improving complex banking and finance data structures. Our Data Engineers find themselves working on a broad range of data-centric technologies across the major cloud providers such as Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP). While our teams have commonly used Python, SQL, Java, and JavaScript as well as a small amount of C#, we expect engineers to be agnostic to technology--valuing their ability to be adaptable and learn quickly.

After creating the machine learning model, we can use the Flask framework to create API for web applications. Here I will teach you how to deploy the flask app to Heroku using docker and GitHub actions. With Docker and Github actions, you can create CI/CD pipeline for your machine learning project. Github action is used to create CI/CD pipeline. CI/CD means continuous integration and continuous deployment.

How do we need to detect outliers? How do we need to treat the outliers? An outlier is that datapoint or observation which behaves very differently from the rest of the data. If we are finding the average net worth of a group of people, and if we find Elon Musk in that group, then the complete analysis will go wrong because of just one outlier. This is a reason why outliers should be treated properly before building a machine learning model.

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Algorithms have helped mathematicians perform fundamental operations for thousands of years. The ancient Egyptians created an algorithm to multiply two numbers without requiring a multiplication table, and Greek mathematician Euclid described an algorithm to compute the greatest common divisor, which is still in use today. During the Islamic Golden Age, Persian mathematician Muhammad ibn Musa al-Khwarizmi designed new algorithms to solve linear and quadratic equations. In fact, al-Khwarizmi's name, translated into Latin as Algoritmi, led to the term algorithm. But, despite the familiarity with algorithms today – used throughout society from classroom algebra to cutting edge scientific research – the process of discovering new algorithms is incredibly difficult, and an example of the amazing reasoning abilities of the human mind.

The Mythos Foundation has been established to manage the day-to-day operations of the Mythos blockchain gaming ecosystem decentralized autonomous organization (DAO). With support from industry leaders in web3 gaming, the goal of the Mythos Foundation is to reduce barriers-to-entry for innovative game developers wanting to build thriving play-and-own game economies. The Mythos Foundation also aims to democratize games and allow for players and creators to participate in game value chains through the Mythos ecosystem, which is grounded in the support of multiple blockchains, unified marketplaces, decentralized financial systems and decentralized governance mechanisms. "Mythical has always been a gamer-first platform, and today's announcement signals our commitment to ensuring our community has increased ownership over their gaming experience" Mythos is also announcing the Mythos token (MYTH), an ERC-20 mainnet token with a fixed supply of 1 billion tokens, that will provide web3 game utility and facilitate ecosystem governance, giving gamers, developers, publishers, and content creators the opportunity to participate and contribute to a truly decentralized ecosystem. Mythical Games is the first to adopt MYTH as its native utility token on the Mythical Chain and will use the token on its Mythical Marketplace.