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IIT-Roorkee launches MTech courses in Artificial Intelligence and Data Science

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The Indian Institute of Technology (IIT), Roorkee will be offering two new Masters of Technology (MTech) programmes in Artificial Intelligence (AI) and Data Science from the academic session 2021-22. The programmes will be launched through the recently established Centre for Artificial Intelligence and Data Science (CAIDS) of the institute. Before applying for the programmes, candidates need to register on COAP 2021 portal at coap.iitd.ac.in. As many as 23 faculty members from 15 different departments of the institute have joined CAIDS as joint faculty of the centre. Candidates must have BE/BTech/Integrated MSc or equivalent degree in any engineering course to be able to apply.


Data Scientist - Decision Science

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Oura is an award-winning and fast-growing startup that helps people track all stages of sleep and activity using the Oura Ring and connected app. By providing daily feedback and practical steps to inspire healthy lifestyles, we've helped hundreds of thousands of people improve their sleep, understand their bodies, and transform their health. We're on a mission to empower every person to own their inner potential, and we're seeking candidates who want to make an impact on our journey. We are looking for a Data Scientist to join our Decision Science team in North America. You will work closely with marketing, product, science and software teams to uncover insights and enable data-driven decision making across all areas of the company.


Senior Data Engineer

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Amazon's Transportation Risk and Compliance (TRC) Team protects Amazon's various transportation businesses by implementing scalable risk management solutions that foster continued business growth. To support the business, we build tools to digitize evidence collection to streamline the audit experience for our transportation partners. We are seeking a seasoned senior Data Engineer who can lead other data engineers, business analysts, and software development engineers to build the most advanced data architecture and products at Amazon and in the world. This mandates building highly available and scalable distributed systems. In this role you will be responsible for designing and delivering large data technical solutions across the TRC organization.You will define and help launch innovative analytical applications used by Product Management, Operations, Auditors, other Dev teams, and Executives with a direct impact on the design, architecture, and implementation of flagship products that customers love and use every day.


Gartner predicts data storytelling will dominate BI by 2025

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Automated data storytelling is the future of analytics. Its rise, meanwhile, could signal the demise of self-service analytics. That was the premise of a presentation by James Richardson, a research director at Gartner who spoke on Feb. 24 during a virtual conference hosted by data storytelling vendor Narrative Science. According to Gartner, data storytelling will be the most widespread means of consuming analytics by 2025. In addition, by then a full 75% of data stories will be automatically generated using augmented intelligence and machine learning rather than generated by data analysts.


Ml874/Data-Science-Cheatsheet - AI Summary

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Update (2019-12-18): The Data Science Cheatsheet has evovled into a book! Data Science Cheatsheet This cheatsheet is currently a 9-page reference in basic data science that covers basic concepts in probability, statistics, statistical learning, machine learning, big data frameworks and SQL. The cheatsheet is loosely based off of The Data Science Design Manual by Steven S. Skiena and An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. Update (2019-12-18): The Data Science Cheatsheet has evovled into a book! This cheatsheet is currently a 9-page reference in basic data science that covers basic concepts in probability, statistics, statistical learning, machine learning, big data frameworks and SQL.


Data Scientists and ML Engineers Are Luxury Employees

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I started my career in 2010 after a master in computer science. During my studies I got hooked by software engineering. It can be really fascinating! You get to build stuff out of nothing. You start from a virtual blank sheet and you can end up with an empire.


Mathematical Laws to know as a Data Scientist.

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Zipf's law was created for quantitative linguistic, which states that given some natural language dataset corpus, any word's frequency is inversely proportional to its frequency table rank. Thus the most frequent word will occur approximately twice as often as the second most frequent word, three times as often as the third most frequent word. For example, in the previous Spotify dataset, I would try to split all the words and punctuation to count them. Below is the top 12 of the most common words and their frequency. When I sum all the word that exists in the Spotify corpus, the total is 759389.


When his hobbies went on hiatus, this Kaggler made fighting COVID-19 with data his mission

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Most medical articles have methods & results sections and matches in those sections are more important. I had little to no expectations entering this competition, so I wouldn't say I was surprised by anything. It was great to see so many smart and capable people all working together to try to help in whatever way they could. All of the work is driven by the Kaggle platform. The list of notebooks cover all the submissions for Round 1 and Round 2 of the CORD-19 challenge. All of the notebooks are in Python.


AI 50 2021: America's Most Promising Artificial Intelligence Companies

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The Covid-19 pandemic was devastating for many industries, but it only accelerated the use of artificial intelligence across the U.S. economy. Amid the crisis, companies scrambled to create new services for remote workers and students, beef up online shopping and dining options, make customer call centers more efficient and speed development of important new drugs. Even as applications of machine learning and perception platforms become commonplace, a thick layer of hype and fuzzy jargon clings to AI-enabled software.That makes it tough to identify the most compelling companies in the space--especially those finding new ways to use AI that create value by making humans more efficient, not redundant. With this in mind, Forbes has partnered with venture firms Sequoia Capital and Meritech Capital to create our third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations. To be considered, businesses must be privately-held and utilizing machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language) or computer vision (which relates to how machines "see"). AI companies incubated at, largely funded through or acquired by large tech, manufacturing or industrial firms aren't eligible for consideration. Our list was compiled through a submission process open to any AI company in the U.S. and Canada. The application asked companies to provide details on their technology, business model, customers and financials like funding, valuation and revenue history (companies had the option to submit information confidentially, to encourage greater transparency). Forbes received several hundred entries, of which nearly 400 qualified for consideration. From there, our data partners applied an algorithm to identify 100 companies with the highest quantitative scores--and that also made diversity a priority. Next, a panel of expert AI judges evaluated the finalists to find the 50 most compelling companies (they were precluded from judging companies in which they have a vested interest). Among trends this year are what Sequoia Capital's Konstantine Buhler calls AI workbench companies--building of platforms tailored to different enterprises, including Dataiku, DataRobot Domino Data and Databricks.


How Data, Analytics & AI Shaped 2020, and Will Impact 2021 - InformationWeek

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The IT enterprise may have started the year stalled on its efforts to deploy at scale production machine learning and artificial intelligence projects, but that didn't last long. The global pandemic's impact included serving as a catalyst to accelerate any number of IT projects for a new way of doing business, and those included AI and automation. The shift to working remotely for so many desk workers necessitated a change in how to do business, sure. But the shift to remote work coincided with a giant spike in demand for customer service and support. For instance, at the consumer bank, who was answering the incoming calls from customers about whether stimulus checks had arrived or cleared?