Learning Verses Efficiency
This article in the Harvard Business Review is worth reading. It suggests that the drive to create efficient data science teams by employing specialists e.g. researchers, data engineers, machine learning experts, inference scientists etc. is the wrong approach. By narrowing the scope of the individual and creating efficiencies, you are removing the opportunity to learn and develop new capabilities.https://hbr.org/2019/03/why-data-science-teams-need-generalists-not-specialists
Would you like to join the judging panel for the International Data Science Awards 2019?
There was just one award made in 2018, Data Science Writer of the Year. This year there will be ten awards.
learn Python for data science online
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S2DS London 2019 applications are now open
Science to Data Science London 2019 applications close soon. 5 weeks of company-led commercial data science experience, to help you transition from academia to industry, all with free on-site accommodation
5 Weeks Gaining Commercial Data Science Experience: S2DS Journeys
Bridge the gap between education and the commercial role of a Data Scientist. Add value to a business, whilst acclimatising to the pace, pressures, and structures that separate commercial environments from academia. - S2DS
Customer Behaviour Predictive Analytics
Some of the key challenges for retail firms are – improving customer conversion rates, personalizing marketing campaigns to increase revenue, predicting and avoiding customer churn, and lowering customer acquisition costs. These can be tackled with deeper, data-driven insights on the customer.
HG Data becomes HG Insights ahead of Big Data World 2019 Executive VP Tim Royston-Webb to give keynote address
HG Data, the global leader in technology intelligence and founder member of the Data Science Foundation has announced its new company name, HG Insights, ahead of this month’s Big Data World conference at ExCel London. The company’s Executive Vice President of Strategy, Tim Royston-Webb, will be giving a keynote presentation at this year’s event which will see the official launch of the new HG Insights Platform, with next generation technographics that boost business intelligence and ignite customer growth.
AI & Big Data Expo 2019, Discount for Data Science Foundation Members
The Data Science Foundation is partnering with the AI & Big Data Expo World Series. We are pleased to offer a 30% discount to members of the foundation to the event at Olympia 25-26 April 2019. An email with the discount code will be sent to you.
World Summit AI Americas 10th - 11th April
Data Science Foundation is delighted to be partnering with World Summit AI Americas, an exclusive gathering of the major AI players, 1000 delegates, and 60 industry-disrupting AI brains as speakers, for two days of mind-boggling innovation, heated discussions on AI ethics and AI4good, applied solutions for enterprise, hands-on workshops, knowledge sharing, networking and entertainment.
In a field as complex and promising as data science, why go it alone when you can collaborate with a top UK university which houses the Jean Golding Institute (JGI) for Data Science and Data Intensive Research?READ MORE
Tim Berners-Lee has marked the 30th anniversary of submitting his proposal for the world wide web with a BBC interview in which he warns of "nastiness and misinformation spreading."READ MORE
But the goal of data science is not to execute. Rather, the goal is to learn and develop profound new business capabilities.READ MORE
China, Russia, and the United States are approaching the long-term strategic potential of artificial intelligence very differently. The country that gets it right will reap huge military benefits.READ MORE
A full 40 per cent of tech companies describing themselves as "AI startups" had no evidence of any machine-learning tech "material" to what the firms actually did, a report by VC investor MMC VenturesREAD MORE
As data becomes increasingly intrinsic to the workings of corporate and everyday life, further integration is needed in the analytic community to drive more powerful data simulation and analysis, to link theory and experimentation, and to better extend the reach and results of big data.READ MORE
Mark Twain once said, “Data is like garbage. You’d better know what you are going to do with it before you collect it.” This gives data science teams food for thought.READ MORE
I believe the job of data scientist as we know it today will be barely recognizable in five to 10 years. Instead, end users in all manner of economic sectors will work with data science software the way non-technical people work with Excel today.READ MORE
One of the problems in society that AI decision-making was meant to solve, was bias. After all, aren’t computers less likely to have inherent views on, for example, race, gender, and sexuality?READ MORE
With applicability of artificial intelligence and machine language becoming pervasive across various sectors in India and around the world, noted tech giants are now open-sourcing more and more of their AI and ML projects.READ MORE
2018 was a year of reckoning for artificial intelligence (AI), proving that it's here to stay and will soon be all around us. Although the hype was at an all-time high, Deloitte’s State of AI in the Enterprise 2018 report showed that 82% of early adopters of AI saw positive ROI, and 63% adopted machine learning (ML) as a key technology in 2018.READ MORE
Unstructured Data/Big Data can be turned into Smart Data using data analytics tools that utilizes advanced artificial intelligence (AI) and machine learning (ML) algorithmsREAD MORE
Any device that can perceive its environment and takes actions that maximize its chance of success at some goal is engaged in some form of artificial intelligenceREAD MORE
Nowadays organizations are starting to realize the importance of using more data in order to support decision for their strategies. The size of data in world is growing day by day. Data is growing because of vast use of internet, smart phone and social network. Big data is a collection of data sets which is very large in size as well as complex. Generally size of the data is Petabyte and Exabyte. Traditional database systems are not able to capture, store and analyze this large amount of data. As the internet is growing, amount of big data continue to grow. Big data analytics provide new ways for businesses and government to analyze unstructured data. Nowadays, Big data is one of the most talked topic in IT industry. It is going to play important role in future. Big data changes the way that data is managed and used. Some of the applications are in areas such as healthcare, defense, traffic management, banking, agriculture, retail, education and so on. Organizations are becoming more flexible and more open. New types of data will give new challenges as well.READ MORE
The biggest challenge of genetic research lies in significant and intellectual analysis of the large and complex data sets generated by the cutting edge techniques like massively parallel DNA sequencing and genome wide analysis. Statistical analyses are the most important of such experimental data. When the data are not normally distributed and using non numerical (rank, categorical) data then use the nonparametric test for exact result of research hypothesis. Order statistics are among the most fundamental tools in non-parametric statistics and inference. Non parametric test does not depend upon parameters of the population from which the samples are drawn, no strict assumption about the distribution of the population. Nonparametric tests are known as distribution free test also because their assumptions are less and weaker than those connected with parametric test. Nonparametric test does not follow probability distribution. To analyze microarrays and genomics data several non-parametric statistical techniques are used like Wilcoxon’s signed rank test (pre-post group),Mann-Whitney U test (two groups) or Kruskal-Wallis test (two or more groups).Importance of this paper is to look at the non-parametric test how to use in genetic research and provide the understanding of these testREAD MORE
This paper discusses the role of the data scientist, what a data scientist is, and the set of skills needed to become one.READ MORE
Ultimately, the widespread adoption of automation and robotics, as well as the rise of artificial intelligence will have profound impacts on the world, particularly in terms of human employment and even the global economy, such as the questions asked by Martin Ford, in his book, Rise of the Robots. Martin Ford suggests the outlook is bleak for millions of workers who define their self-worth in terms of their employment. Increasingly workers will no longer be exploited by those in control of capital and intelligent machines, they will be irrelevant to them.READ MORE
This paper focuses on how AI is disrupting the insurance sector. Starting from the conventional insurance process, we will move through the specific novelties AI is introducing in the field in order to understand how AI is completely changing the way people buy and think of insurance products. Finally, an eight-group classification is proposed for the insurtech ecosystem.READ MORE
Big data is often approached as a mere technical problem, while many times projects fail because of lack of strategic focus. Implementing the right process may help companies to efficiently run analytics works and for this reason, the paper proposes a few concepts that can support the organizational development of a big data blueprint. Three main ideas will be outlined here: the data lean approach, the maturity map, and different organization models for a data team.READ MORE
Unless you’ve been living under that proverbial rock, you’ve at least heard of cryptocurrency – those digital, non-corporeal monetary units that have the world abuzz these days. Bitcoin is probably the most obvious such crypto coin, but there are plenty of others that have sprung up in the wake of bitcoin’s success, such as Ethereum and Ripple. However, chances are good that unless you’re a financial expert, and possibly even if you are such an expert, you’re not all that clear on what cryptocurrency is, how it works, the risks involved, or even why or how to accept it as payment. Within this guide, we’ll explore those topics and more to help you understand how to buy, use and invest with cryptocurrency. To many people, the term “cryptocurrency” might seem pretty self-explanatory, but if you take a deeper look at the subject, you’ll likely find that it’s more complicated than it might seem at first glance. After all, crypto coins have virtually nothing in common with traditional currency, other than acting as a store of value. Even that similarity can be questionable. So, what is a cryptocurrency?READ MORE
Geospatial Big Data analytics are changing the way that businesses operate in many industries. Although a good number of research works have reported in the literature on geospatial data analytics and real-time data processing of large spatial data streams, only a few have addressed the full geospatial big data analytics project lifecycle and geospatial data science project lifecycle. Big data analysis differs from traditional data analysis primarily due to the volume, velocity and variety characteristics of the data being processed. One motivation in introducing a new framework is to address these big data analysis challenges. Geospatial data science projects differ from most traditional data analysis projects because they could be complex and in need of advanced technologies in comparison to the traditional data analysis projects. For this reason, it is essential to have a process to govern the project and ensure that the project participants are competent enough to carry on the process. To this end, this paper presents, new geospatial big data mining and machine learning framework for geospatial data acquisition, data fusion, data storing, managing, processing, analysing, visualising and modelling and evaluation. Having a good process for data analysis and clear guidelines for comprehensive analysis is always a plus point for any data science project. It also helps to predict required time and resources early in the process to get a clear idea of the business problem to be solved.READ MORE
The hype about AI makes it difficult for experienced investors to understand where the real value and innovation in the technology are to be found. This paper helps to bring some clarity to what is happening on the investment side of the artificial intelligence industry.READ MORE
The objective of this paper is to provide a comprehensive perspective on the advancements in the area of Artificial Intelligence and how the infusion of cognitive customer engagement can positively impact the infamously unpredictable consumer cyclical retail industry.READ MORE
Data security has never been a more important consideration for consumers or for the businesses they patronize and partner with. It’s also never been more difficult to ensure. Every single day, consumers’ personal, health and financial information is at risk of theft. This can lead to identity theft, and to serious financial ramifications. While military-grade encryption on websites and through smartphone and tablet apps can be an important precaution, it’s just a Band-Aid. More must be done. Blockchains may hold the key to ensuring data security, but how does the technology that underpins bitcoin and other cryptocurrencies ensure data security for consumers and businesses?READ MORE
Blockchains, a technology behind the success of cryptocurrency, symbolize an great application of cryptography and technology to one of the biggest problems of record-keeping for financial institutions, and they may create some far-reaching changes in method of transactions. Many big institutions of the industry had invested billions in the new technology, and many other industries have proposed new methods of transactions and ownership shift by use of the blockchains. This article studies the possible implications of the changes for stakeholders into the business like investors, employees, auditors, external shareholders, customers and other parties. The greater transparency, better transaction, accuracy, greater liquidity and lower cost offered by the technology may considerably turn over the uses and way of working of the industries.READ MORE
This article is about the future of AI. The following proposed list does not want to be either exhaustive or truth-in-stone, but it comes from a series of personal considerations that might be useful when thinking about the impact of AI on our world.READ MORE
Unless you’ve been stuck under that proverbial rock for a few years, you’ve at least heard of the Internet of Things (IoT) and how it is connecting us in new and interesting ways. The rise of the smart home is one way that the IoT is changing things for people around the world – homes filled with devices that can communicate with one another, with people living in the home, and even with outside third parties. However, this technology is not constrained just to our homes. It’s growing in terms of both scope and capabilities. Enter the smart city, where the Internet of Things will impact everything from lighting to the flow of traffic through urban centresREAD MORE
Data is everything. In fact, thieves are now targeting consumer and business information rather than financial assets, simply because there is so much more value in data. Find out more about how GDPR is changing the way we all work with data in the midst of this Information age.READ MORE
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