Driven by developments in artificial intelligence and big data, the whole financial industry is undergoing a fundamental change that will become even more pronounced in the coming years. The associated changes entail many opportunities, but also numerous risks. It is already foreseeable that there will be both winners and losers, especially since the degree of maturity of the use of artificial intelligence in banks is very different.
But how can a bank actually notice that it is being…
Added by Dr. Dimitrios Geromichalos on June 25, 2018 at 12:30am — No Comments
Privacy!! does it really exist in todays time, when technology allow to monitor even your personal movement in your dark bedroom through solid walls.
Lets race for DataIntelligence this is what is mantra for every company on planet today. Do we really have privacy any more. What all data and upto what extend getting collected more then 90% of us are not even aware.
Some sources from internet (reliable sources) claims…
ContinueAdded by Vinod Sharma on June 24, 2018 at 10:30pm — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Announcement
Added by Vincent Granville on June 24, 2018 at 3:00am — No Comments
DataMelt computational platform for data analysis organized its Java documentation:
Added by jwork.ORG on June 23, 2018 at 5:24pm — No Comments
The main components of systems theory that readers might remember are “inputs,” “processes,” and “outputs.” The part that tends to get neglected is “feedback mechanisms.” These mechanisms tell the system the extent to which operations fit the environment. If there is lack of fitness, there is stress. One adaptive impulse is to make processes more complex and intelligent - i.e. sometimes described as the fight response. Another impulse is to give up and run away - i.e. the flight…
ContinueAdded by Don Philip Faithful on June 23, 2018 at 9:00am — 1 Comment
Michael Nielsen provides a visual demonstration in his web book Neural Networks and Deep Learning that a 1-layer deep neural network can match any function . It is just a matter of the number of neurons to get a prediction that is arbitrarily close – the more the neurons the better the approximation. There is the Universal Approximation Theorem as well that supplies a rigorous proof of the same.But the known issues…
Added by Ashok Chilakapati on June 22, 2018 at 2:30pm — No Comments
In this post, Encoding high cardinality text data for a ML algorithm, the author compares 4 ways to encode non-numerical tabular data. This skill is quite useful and necessary to be able to use years worth tabular data in a machine learning and deep learning algorithms.
One of the ideas, Character Encoding is an…
ContinueAdded by Nitin Pasumarthy on June 22, 2018 at 12:30am — No Comments
In this article by Maxim Lapan, the author of Deep Reinforcement Learning Hands-On,we are going to discuss about gradients in PyTorch.
Gradients support in tensors is one of the major changes in PyTorch 0.4.0. In previous versions, graph tracking and gradients accumulation were done in a separate, very thin class Variable, which worked as a wrapper around the tensor and automatically performed saving of the history of computations in order to be able to…
ContinueAdded by Packt Publishing on June 22, 2018 at 12:30am — No Comments
Interested question posted on Quora recently. Here is my take on this.
Just put the next buzz word on your resume when you graduate, maybe AI engineer? I completed my PhD in computational statistics 25 years ago. It was in fact data science (image remote sensing), but under a different name. I changed my job title from statistician to data scientist many years ago, and I may dot it again if needed. There is more and more data to process, so the need will grow, but it will grow very…
ContinueAdded by Vincent Granville on June 21, 2018 at 12:30pm — No Comments
TLDR: Neural Networks are powerful but complex and opaque tools. Using Topological Data Analysis, we can describe the functioning and learning of a convolutional neural network in a compact and understandable way. The implications of the finding are profound and can accelerate the development of a wide range of applications from self-driving everything to GDPR.
Neural networks have demonstrated a great…
Added by Jonathan Symonds on June 21, 2018 at 9:30am — No Comments
What You Need to Know about Machine Learning
By Gabriel A. Canepa
This eBook offers you the perfect place to lay the foundation for your work in the world of Machine Learning, providing the basic understanding, knowledge, and skills that you can build on with experience and time.…
ContinueAdded by Packt Publishing on June 21, 2018 at 12:50am — 2 Comments
Over the past decade, we have seen a shift towards virtualization, a stepping stone to complete cloud utilization. However, even by leveraging virtualization, you still need the appropriate building blocks for a private cloud environment. This involves going beyond simply virtualizingcompute and other central data center subsystems (i.e., network and storage), and requires you to enable flexible APIs in order to automate resource provisioning and…
ContinueAdded by lakshmi yarlagadda on June 20, 2018 at 11:30pm — No Comments
Digital world is all around us! Disruptive Business Models is the new phenomenon! It means different things (not just internet of things) to different people and businesses.
Some industries are traditionally slow in adapting new technologies. For example, AOVC (Asset Oriented Value Chains – Natural Resources, Metals and Chemicals) have not explored digital to it’s full potential. Analytics is one of the key components of this revolution. It it not just about capturing…
ContinueAdded by Amit Supe on June 20, 2018 at 10:00pm — No Comments
If you keep up with the latest trends in the business world, then Data Science is a term that appears frequently nowadays. It is a steadily growing field and newer developments keep occurring as well. Data Science is responsible for multiple benefits for varying business industries. Small and large businesses alike are catching up; discovering high potential for growth using data analytics.
Businesses that seek to improve their solutions for customers by…
ContinueAdded by VAMSI NELLUTLA on June 20, 2018 at 5:30pm — No Comments
Gartner’s recently released “Magic Quadrant for Industrial IoT Platforms” outlines how organizations can leverage the Internet of Things (IoT) to drive their digital transformation initiatives. In particular, Gartner believes that “By 2020, on-premises Internet of Things (IoT) platforms coupled with edge computing will account for up to 60% of industrial IoT (IIoT) analytics, up from less than 10% today.”[1]
More real-time sensor and…
ContinueAdded by Bill Schmarzo on June 20, 2018 at 1:30pm — No Comments
This article was written for The Data Incubator by Jay Kaiser, a Fellow of our 2018 Winter cohort in Washington, DC.
The 2016 Presidential Election was, in a single word, weird. So much happened…
Added by Michael Li on June 20, 2018 at 10:30am — No Comments
This article comes from Deep Learning Patterns.
Note to reader: Diving into this material here can be a bit overwhelming. One way though to get an understanding of the thought process is to follow the Intuition Machine blog.
Deep Learning Architecture can…
ContinueAdded by Emmanuelle Rieuf on June 20, 2018 at 8:30am — No Comments
We discuss a new approach for selecting features from a large set of features, in an unsupervised machine learning framework. In supervised learning such as linear regression or supervised clustering, it is possible to test the predicting power of a set of features (also called independent variables by statisticians, or predictors) using metrics such as goodness of fit with the response (the dependent variable), for instance using the R-squared coefficient. This makes the process of feature…
ContinueAdded by Vincent Granville on June 20, 2018 at 5:00am — 3 Comments
Bill is the Editorial Director for Data Science Central, and President and Chief Data Scientist at Data-Magnum, providing predictive analytics and big data infrastructure projects as a service. Bill has been an active commercial predictive modeler since 2001.
In this series consisting of six parts so far (and…
ContinueAdded by Vincent Granville on June 19, 2018 at 8:30pm — No Comments
In this study, we predict the outcome of the football matches in the FIFA World Cup 2018 to be held in Russia this summer. We do this using classification models over a dataset of historic football results that includes attributes from the playing teams by rating them in attack, midfield, defence, aggression, pressure, chance creation and building ability. This last training data was a result of merging international matches results with AE games ratings of the teams…
ContinueAdded by Estefany Torres on June 19, 2018 at 8:30am — 10 Comments
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