Cancer Research Special Interest Group
Four highly qualified people have agreed to join the Special Interest Group within hours of this article being published. Our target is to launch the group with at least 12 members. Thank you for the support, a progress update and an agenda for the group will be published at the beginning of February.
The Perfect Storm. How the Confluence of AI, Robotics Technology and Big Data Will Affect Human Employment
Here is an interesting article in Wired on 'Rise of the Robots' by Martin Ford: https://www.wired.com/brandlab/2015/04/rise-machines-future-lots-robots-jobs-humans/ The book is extremely well written and worth purchasing: https://www.amazon.co.uk/Rise-Robots-Technology-Threat-Unemployment/dp/1780747497
Python for data science course
HoningDS.com offers the best online Data Science training. Get trained in Python, R, Statistics and Machine Learning by real time professional. We offer online course for every aspiring Data Scientist in any part of the world. Get hands-on experience using real time projects and become a Data Scientist.
Data Forecast 5 2019
Data Forecast 5 2019We are asking our members to predict the most likely developments in data use and data technology in 2019.We will identify five key trends in the answers submitted and publish them on the Data Science Foundation website. You could think along the following lines.· Which fringe technologies will become mainstream?· How will organisations change the way they manage and use their data?· What will be the driving influences on data analytics?· Are we likely to see huge advances created by the convergence of technologies? · Should the public at large be concerned about potential technical advances or data usage in 2019?
Discussion on the use of graph theory/network science in the field of business intelligence.
Update: I had a lot of great answers when I posted this question on Twitter @ToriTompkins.Graph Theory has some good applications when resolving dependencies between source files. This involves determining what processes can be run after a source file has loaded by querying for all associated nodes. Collaborative working. For example some issues on GitHub are tagged by multiple users. Social network analysis can be used to identify shortest paths, influencers, cliques etc.Many processes in business intelligence have complicated and moving parts for example percurement, contracts or fraud. Graph theory can be utilised to uncover hidden connections.Any more suggestions are welcome!
The Data Science Foundation is source of information on big data techniques and practices. We review and publish industry news, comment and white papers submitted by our members. We are recruiting editors and contributors to work with us on this site.
Cancer Research Special Interest Group
The Data Science Foundation will launch a cancer research discussion group within the next couple of months. The idea is to bring together people with relevant expertise and or access to resources and to initiate a discussion on how the group might contribute to work being done in this field.
Data Science Writer of the Year 2018
Francesco Corea is recognised as the Data Science Foundation, Data Science Writer of the Year 2018
AI and Speech Recognition: A Primer for Chatbots
Conversational User Interfaces (CUI) are at the heart of the current wave of AI development. Although many applications and products out there are simply “Mechanical Turks” — which means machines that pretend to be automatized while a hidden person is actually doing all the work — there have been many interesting advancements in speech recognition from the symbolic or statistical learning approaches. In particular, deep learning is drastically augmenting the abilities of the bots with respect to traditional NLP (i.e., bag-of-words clustering, TF-IDF, etc.) and is creating the concept of “conversation-as-a-platform”, which is disrupting the apps market.
Forcast 5 2019
We are asking our members to predict the most likely developments in data use and data technology in 2019. We will identify five key trends in the answers submitted and publish them on the Data Science Foundation website.
Is There Such Thing As Too Much Data?
In today’s business environment, data rules. Because it is used to determine every strategic move at each level of an organization, it makes sense that you should collect as much information as possible right? I argue that this is actually not the case! Like most things in life, too much of anything is bad- data included. The two major reasons why I argue this position are the paradox of choice and its causal relationship to analysis paralysis. If you have found yourself overwhelmed with a data set before and thought, “Where in the world do I even begin?” then this is the article for you. So grab a seat, pour yourself a cup of coffee, and get ready to never look at data the same way again. This article explores the idea that too much data can actually be detrimental to analysts.
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
In this article, we list 10 important data science projects that every e-commerce is using to ensure healthy business.READ MORE
The public thinks that human-level AI is likely to cause more harm than good, a new report has shown.READ MORE
Yinyin Yuan and colleagues at the Institute of Cancer Research in London built an AI to look for differences in tumour cell shape.READ MORE
Basis AI announced today that it has raised S$8.2 million (US$6 million) in seed funding from high-profile investors Temasek and Sequoia India.READ MORE
Columbia's Andrea Califano has developed a highly-predictive computer platform that can analyze all tumor types and predict which drug or drugs will be most effective in treating them.READ MORE
For the first time, a group of researchers from Charité - Universitätsmedizin Berlin have determined general population quality of life normative data for 15 individual countriesREAD MORE
Meeshkan allows data science teams to train, test, and deploy ML models right from Slack. Meeshkan is free and can be installed into your Slack workspace in less than a minute. I have been following them for a while now and they are amazing, pushing forward the boundaries of ML development! Upvote them on Product Hunt and start using the platform! https://www.producthunt.com/posts/meeshkan-2READ MORE
According to LinkedIn, as of August 2018 in the U.S., the tech industry is experiencing a shortage exceeding 150,000 of people with data science skills. And with firms like IBM forecasting 28 percent growth in the number of AI- and analytics-related job listings, it’s a virtual certainty that corporate recruitment won’t get any easier in the months ahead.READ MORE
Dataiku wants to turn buzzwords into an actual service. The company has been focused on data tools for many years, before everybody started talking about big data, data science and machine learning.READ MORE
Data science and machine learning are often associated with mathematics, statistics, algorithms and data wrangling. While these skills are core to the success of implementing machine learning in an organization, there is one function that is gaining importance – DevOps for Data Science.READ MORE
As the lifesciences sector continues to evolve, importance of optimizing quality related to capital investment decision increases among companies.READ MORE
The Analysis presents the study of Global Big Data in Healthcare facilitating the regional and country wise analysis covering the strategic analysis of each market player and the market share they holdREAD 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
Traditional sources of energy are in decline and the world is shifting towards renewable forms of energy. There are around 50 solar power plants in India. These power plants incorporate solar power grids, inverters, batteries and various sensors for monitoring and control. There is a requirement for efficiency and to detect system faults; to this end the data generated by sensors must be constantly monitored and analysed. With cloud service technology, solar grids sensors can be connected to remote monitoring facilities by utilizing Internet of Things (IOT) technology. The huge volumes of data produced by sensors is now manageable, and with Big Data techniques and MapReduce algorithm, it is not only possible to store and analyse data, but predict potential problems. This paper investigates ways to store, analyze and visualize the data produced by solar sensors.This paper aims to analyze following things: 1) Detecting Flaws in solar power plants/farms 2) Analyzing Power generated 3) Visualizing the resultsREAD MORE
The Data Science Foundation is your source of information on big data techniques and practices. We review and publish industry news, comment and white papers submitted by our members. Our information includes various data science courses available and offered by different universities and online data science course administrators as well as information on data science training & certification. We are recruiting editors and contributors to work with us on this site. Get in touch.
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