Friday, December 20, 2019
Business Intelligence and Analytics 43
1 Google’s New Explainable AI Service
https://www.kdnuggets.com/2019/12/googles-new-explainable-ai-service.html
Artificial intelligence is set to transform global productivity, working patterns, and lifestyles and create enormous wealth.
Research firm Gartner expects the global AI economy to increase from about $1.2 trillion last year to about $3.9 Trillion by 2022, while McKinsey sees it delivering global economic activity of around $13 trillion by 2030.
2 Is deep learning a game changer for marketing analytics?
http://mitsloanexperts.mit.edu/is-deep-learning-a-game-changer-for-marketing-analytics/
Deep learning is delivering impressive results in AI applications. Apple’s Siri, for example, translates the human voice into computer commands that allow iPhone owners to get answers to questions, send messages, and navigate their way to and from obscure locations. Automated driving enables people today to go hands-free on expressways, and it will eventually do the same on city streets. In biology, researchers are creating new molecules for DNA-based pharmaceuticals.
3 The Most In Demand Tech Skills for Data Scientists
https://www.kdnuggets.com/2019/12/most-demand-tech-skills-data-scientists.html
In fall of 2018 I analyzed the most in demand skills and technologies for data scientists. That article resonated with folks. It has over 11,000 claps on Medium, was translated into several languages, and was the most popular story on KD Nuggets for November 2018.
4 Can AI-Fueled Digital Marketing Change Landscape and Fuel Growth?
https://martechseries.com/mts-insights/guest-authors/can-ai-fueled-digital-marketing-change-landscape-fuel-growth/
Digital Marketing is not as easy as it reads. It is facing numerous challenges. With everyday growing websites, and everyone competing to rank on the first pages of SERPs, the competition has become tougher than ever. However, the rising of challenges has also given the birth of rising of new technologies. Nowadays, terms like Blockchain, Artificial Intelligence, Internet-of-Things, Machine Learning, Data Science, etc. have found their strong places in human minds across various industries at a global level.
5 Model beats Wall Street analysts in forecasting business financials
http://news.mit.edu/2019/model-beats-wall-street-forecasts-business-sales-1219
Knowing a company’s true sales can help determine its value. Investors, for instance, often employ financial analysts to predict a company’s upcoming earnings using various public data, computational tools, and their own intuition. Now MIT researchers have developed an automated model that significantly outperforms humans in predicting business sales using very limited, “noisy” data.
6 5 Ways to Apply Ethics to AI
https://www.kdnuggets.com/2019/12/5-ways-apply-ethics-ai.html
I have researched this topic quite a lot, and during that time I have found a number of stories that made a huge impression on me. Here are six more lessons based on real life examples that I think we should all remember as people working in machine learning, whether you’re a researcher, engineer, or a decision-maker.
7 How to Avoid All-or-Nothing Thinking in Your Tech Strategy
https://sloanreview.mit.edu/article/how-to-avoid-all-or-nothing-thinking-in-your-tech-strategy/
Companies’ failure to innovate exposes them to risk and has a huge impact on the global economy.
8 What Employees Tell Us About Automation and Re-skilling
https://sloanreview.mit.edu/article/what-employees-tell-us-about-automation-and-re-skilling/
There is an ever greater focus on the impact of automation on work and what it will mean for jobs. Certain kinds of routine work are on the front lines, including the analytical activities of administrative assistants and bank cashiers, and the manual jobs of warehouse assistants, assembly line workers, and delivery drivers. Many tasks within these jobs are likely to be automated: For instance, delivery workers now scan packages and generate automated driving statistics.
9 8 Superstar Video Chat & Conferencing Apps for Business
https://www.searchenginejournal.com/video-conferencing-chat-apps/334977/
As marketers, we constantly focus on what we’re doing and why we’re doing it. We need to make sure the tasks we undertake (the what) contribute to purposeful goals that make a difference (the why). While this approach makes sense, we often neglect the process; namely how we do what we do.
10 4 Easy Tricks for Improving Your Bounce Rate in 2020
https://www.business2community.com/consumer-marketing/4-easy-tricks-for-improving-your-bounce-rate-in-2020-02269121
Do you have an unusually high bounce rate? Are you looking for a way to keep customers on your website? Are you just now hearing the term bounce rate and want to know more? If you answered “yes” to any of these questions, you’re in the right place.
11 In the New Year, Try These 8 Things to Stay Constantly Improving at Work
https://www.business2community.com/workplace-culture/in-the-new-year-try-these-8-things-to-stay-constantly-improving-at-work-02268932
With the changing seasons, holiday decorations, and cheery music flowing from seemingly every storefront, one thing is clear — the end of the year is upon us, and 2020 is not far away. Here are some ways that you can stay constantly improving once 2020 arrives
12 Statistics for Data Science in One Picture
https://www.datasciencecentral.com/profiles/blogs/statistics-for-data-science-in-one-picture
There’s no doubt about it, probability and statistics is an enormous field, encompassing topics from the familiar (like the average) to the complex (regression analysis, correlation coefficients and hypothesis testing to name but a few). If you want to be a great data scientist, you have to know some basic statistics. The following picture shows which statistics topics you must know if you’re going to excel in data science.
