Unsupervised investments: Top AI Venture Funds
If you want to see the full list (although not completely updated) here is the link:https://medium.com/@Francesco_AI/unsupervised-investments-i-a-guide-to-ai-investors-d1a6326f71ea
Big Data Strategy: tips and practices
A modified version of this paper has been presented and accepted at an international conference very recently and will be available in a few months time in the " Advances in Intelligence Systems and Computing" series.
What should primary and secondary school educators teach in the age of AI?
I saw another article on my news feed today about what skills the next generation will need to succeed...and which there is little point learning because AI will make the jobs involving those skills redundant. What do people on here think? And why?
What you are too afraid to ask about Artificial Intelligence Part II
I highly recommend reading the work of Numenta, which gives a new perspective on neuroscience and the biological approach to AI
Imagining Myself as a Data Engineer
Kaggle is a great place to start. Plenty of datasets, challenges and competitions https://www.kaggle.com/datasets
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Unsupervised investments: Top AI Venture Funds
This article lists the top VC investing in AI as well as the features and characteristics that made them the best fit for entrepreneurs
Why AI is a great match for your data strategy
2017 was said to be the year of artificial intelligence (AI) thanks to the many leaps and bounds the technology made. It was also the year when its hype-mill went into overdrive. Which is annoying because, behind all the hype and inflated expectations, there are some really great applications of AI that you can take advantage of now, not in the year 3000 – and it’s not all robots, sci-fi and Black Mirror either.
Congratulations to Francesco Corea, the winner of the March Data Science Foundation Contributor Competition
Congratulations to Francesco Corea, the winner of the March Data Science Foundation Contributor Competition. The March Contributors Competition is now closed, the winner of the £50 Amazon gift voucher is Francesco Corea. Thank you all for submitting article and papers. The April competition is now open.
Advances in Data Science 2018: Final Speakers & Discussion Themes
The University of Manchester's Data Science Institute is delighted announce the conference’s final speaker line up and the themes to be discussed our upcoming Advances in Data Science Conference on May 21st and May 22nd in Manchester. “Focusing on Gaussian processes, Deep learning, latent variable models, subspace learning, network models, spatio-temporal models and longituinal data, we will explore the ways in which these methodologies can be used to address challenges faced by those working in the key application areas: Health - Security - Criminology - Discrimination/Bias - Politics - Demographics - Urban Planning - Global Challenges - Social Media – Conservation” The full conference schedule will be available on the Advances in Data Science website on March 30th 2018.
Strata Data Conference | 21-24 May 2018 | London
Strata Data Conferences bring together some of the world's smartest data scientists and business strategists to share new skills, share best practices, and lay a foundation for the future. Learn the techniques and technologies you need to build successful, data-driven projects and organisations at Strata Data Conference. Save 20% on most passes with discount code DSF20 . Early price ends Friday, 6th April.
Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making—and already it is transforming every walk of life. In this report, Darrell West and John Allen discuss AI's application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.READ MORE
Leading scientists have drawn up plans for a vast multinational European institute devoted to world-class artificial intelligence (AI) research in a desperate bid to nurture and retain top talent in Europe.READ MORE
Human spies will soon be relics of the past, and the CIA knows it. Dawn Meyerriecks, the Agency’s deputy director for technology development, recently told an audience at an intelligence conference in Florida the CIA was adapting to a new landscape where its primary adversary is a machine, not a foreign agent.READ MORE
Knowhere launched earlier this month, alongside an announcement that it had raised $1.8 million in venture capital.READ MORE
FT notes that while MBAs are shrinking, analytics masters are a growth marketREAD MORE
Dr Philip Mayne Woodward was a British mathematician, pioneering radar engineer and world-renowned clock-maker.READ MORE
If we want our machines to possess anything approximating human intelligence, maybe we should think about giving them a childhood, too.READ MORE
Researchers from the University of California-San Francisco are able to analyze MRI images using machine learning algorithms for computer-aided prognosis to predict short- and long-term outcomes for patients after acute spinal cord injuries.READ MORE
Using machine learning technique to identify who will respond to certain therapy based on patient's genetic information. This is an example of precision medicine.READ MORE
The annual IAPA Skills and Salary Survey has tracked the rise and rise of the analyst salary, with median salaries now sitting at twice the average Australian’s take home wage in 2017, with an even stronger rise above the norm at the entry and expert ends of the spectrum.READ MORE
Artificial intelligence (AI) is learning to recognize patterns of life-supporting conditions on other worlds.READ MORE
Poor data quality is enemy number one to the widespread, profitable use of machine learning.READ MORE
Last week, World Economic Forum released a paper on how to prevent discrimination of humans in machine learning? In which it provides a framework for developers to understand the potential risks associated with machine learning applications and how to combat marginalisation and discrimination of humans in AI and encourage dignity assurance.READ MORE
The recent controversy about Cambridge Analytica’s use of Facebook data to, allegedly, influence the 2016 US presidential election and, possibly, the UK EU referendum raises an ethical issue, especially for data scientists newly minted from UK universities.READ MORE
This article provides a series of forecasts regarding the development of AI and robotics. We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments. 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. The interesting aspect of those is that are predictions made one year ago, and many turned out to be true.READ MORE
This paper illustrates tips and tools to run a data science practice within an organization. It will also give some tools to understand the stage of data science maturity of the company.READ MORE
Propensity modelling is a statistical approach and a set of techniques which attempts to estimate the likelihood of subjects performing certain types of behaviour (e.g. the purchase of a product) by accounting for independent variables (covariates) and confounding variables that affect such behaviour.READ MORE
This article follows the first piece on machine learning describing how AI interacts with neuroscience, as well as how hardware and chips are getting created and modified to be more efficient for specific AI algorithmREAD MORE
The rapid expansion of Big Data Analytics is forcing companies to rethink their Human Resource (HR) needs. However, at the same time, it is unclear which types of job roles and skills constitute this areaREAD MORE
This paper describes how AI is revolutionizing business modelsREAD MORE
This is paper that explains the basic concepts behind AI as well as common definitions that are needed to be knownREAD MORE
This is a short guide to AI Accelerators and Incubators worldwideREAD MORE
A detailed summary of Pandas CookbookREAD MORE
This paper will provide a description of how AI is changing the insurance industry as well as who are the most-known players in the spaceREAD MORE
This paper defines what big data and data science are and common myths that need to be explained in order to fully understand and use this powerful technology.READ MORE
I am going to briefly present three new roles emerged because of new exponential technologies, i.e., the Chief Data Officer (CDO), the Chief Artificial Intelligence Officer (CAIO) and the Chief Robotics Officer (CRO).READ MORE
The paper describes the architecture of a simple neural network and offers a useful intuition on how it may be used to solve complex nonlinear problems in an efficient way.READ MORE
The periodic table of elements is an atomic organisation based on two axis. The horizontal axis establishes an increasing order based on the atomic number (number of protons) of each element. The vertical arrangement is managed by the electronic configuration and presents a taxonomic structure designed by the electrons of their latest layer . Furthermore, four main blocks arrange the atoms by similar properties (gases, metals, nonmetals, metalloids). Additionally to the number of protons and the electronic configuration, the atoms are characterised by other attributes that are not ascendant nor cyclic in the periodic table of elements. The values of these properties constitute a sample of numbers that represent different atomic magnitudes that distinguish in some how the chemical elements. In this experiment some of these chemical and physical dimensions have been involved in the training of a set of machine learning algorithms to obtain representative clusters of each element.READ MORE
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