Modern Enterprise Data Management in Healthcare
There are proven data and information governance methods and frameworks in existence, but still today, the question is : are they capable enough to promise a fast-advancing but stable, secure and efficient framework for Data Management in an organization? Read more
Mentoring an Apprentice – What are The Best Practices?
How best to implement a mentoring program in an organisation; an effective apprenticeship-mentoring case study. Read more
Data at the workplace – Opportunity for Training Providers
Getting your workforce data-ready will soon be essential for all businesses, regardless of job roles. It may not be compulsory to work with data at the moment; it will be soon. Read more
Release Update for Spark NLP for Healthcare 2.6
Spark NLP for Healthcare 2.6 has just been released. In addition to all the goodies of the latest open-source package, new features are included in this update Read more
JPST Study Shows AI Algorithms Can Be Qualified for Regulated Pharmaceutical Manufacturing
A new study that has been published online in the Parenteral Drug Association’s Journal of Pharmaceutical Science and Technology (PDA JPST), demonstrates that AI algorithms can be qualified for pharmaceutical product and medical device productivity chains. Read more
Data Science Expert Whitehat Analytics Brings Data to Life for EDF
When energy giant EDF wanted to extract new value from its legacy data stores and put it to strategic use, Whitehat Analytics was the partner of choice to design a high-performance cloud platform to serve up data-driven insights across the business. Read more
Identifying Objects and Patterns from Satellite Images
Digital Globe and Airbus Defence and Space are using artificial intelligence to process the large volume of data that satellites produce. Artificial intelligence is used to identify objects, classify objects, and localize some specific classes from an image segment at the pixel level to determine which class it is. Read more
UnifAI Aim to Simplify Artificial Intelligence for Real World Applications
This is the first of 3 short videos that illustrate some of our work, where we will begin to show how anyone with historic data can easily and affordably get involved with AI Read more
Technology: A Pandemic Leadership
Pandemics are not new for society; they threaten our race time and again. SARS, H1N1, Ebola, and more have shown their teeth in the past, but with each such outbreak, we are learning new ways of fighting and managing such unexpected diseases that can potentially kill millions of people. The key differentiator of current pandemic from previous ones is the availability of technology, such as mobile, cloud, analytics, robotics, AI/ML, 4G/5G, and high-speed internet. These technologies are helping us to spread information faster and working to support society. Read more
Understanding Imbalanced Datasets and techniques for handling them
Imbalanced datasets contain valuable data that is often lost in data techniques that aim to balance datasets. In this article, we will look at what an Imbalanced dataset is and various techniques that can be used to handle imbalanced datasets.
Real Time Data Analytics: Mitigating the Risks and the Challenges
While practical benefits of the Real-time data analytics over historic data analytics are obvious, it is also essential to understand and cater for its risks, challenges and limitations.
Understanding Buzzwords in Data Science
Have you come across Data Science jargon and buzzwords such as Artificial intelligence (AI); Machine Learning (ML); Deep Learning (DL); Neural Network (NN) etc.. want to know more about them and how each of them differ? If so then checkout this article, which will give you a brief idea what these are.
INNOVATING THE LEARNING EXPERIENCE THROUGH EDUCATIONAL TECHNOLOGY: A DIGITAL INSIGHT
The Next Generation Digital Learning Environment (NGDLE) is considered as a ecosystem - a learning situation comprising of learning apparatuses and segments that stick to normal guidelines. While the customary Learning Management System (LMS) gives regulatory capacities, the NGDLE is planned to straightforwardly bolster learning.
Knowing all about Outliers in Machine Learning
While working on various dataset to train a Machine Learning model. What is it, that you look for? What is the most important part of the EDA phase? There are certain things which, if they are not done in the EDA phase, can affect further statistical / Machine Learning modelling. One of the answers is to, find “Outliers”.
Underfitting and Overfitting in Machine Learning
Machine learning developers often encounter models that perform well on a data set, but dont live up to expectations when used on unseen or test data. This problem is called Overfitting. If you would like to learn more about Overfitting and how to avoid it, read on.
One of the ways physicians can gain some forewarning of impending heart failure is through the detection of excess fluid in the lungs, and MIT researchers have developed a new machine learning tool that could offer them a helping hand. The algorithm is able to detect severe cases of this condition with a high level of accuracy, and the researchers behind it are hopeful it could be adapted to assist with the management of other conditions, too. Learn more here: https://bit.ly/2HQaKR4READ MORE
I have a Data Cloud Lab and Github too, Ready to contribute someone like you. please send me your resume at firstname.lastname@example.org. I will find out your solution. Thank youREAD MORE
Agree, with the time researchers has found various tools and techniques that today one can do real time data analysis, but again it depends on the person, how (s)he will be using the tools and techniques with respect to the creativity. As to achieve there could be multiple ways, to use right weights & parameters are the most effective part of it.Thanks for sharing this valuable information.READ MORE
Many times, I have seen data science professionals who know very well what is p-values but they struggle to explain it. I have also seen many professionals who don’t want to get into technical details but want to know more and understand why it is so important.READ MORE
This article is very informative and the steps which are been soon can be easily approcable .A lit more effective and efficient way the author tries to summarise the step here.READ MORE
That's a good article and very well explained.I was using EML without realizing it... in form of Random Forest Algorithm.READ MORE
It is really very excellent and eye-catching website. Thanks Nr. Chris for your kind gestures and support to grant me full membership status. I will try my level best to do some extraordinary things for Data Science. Inshaa Allah (God Willing).READ MORE
The Next Generation Digital Learning Environment (NGDLE) is considered as a ecosystem - a learning situation comprising of learning apparatuses and segments that stick to normal guidelines. While the customary Learning Management System (LMS) gives regulatory capacities, the NGDLE is planned to straightforwardly bolster learning.READ MORE
What is the correlation between Data Science and Econometrics.I have been thinking to find out if Data Science can stand alone without Econometrics. Will it rather be wise to say Econometrics forms a better modelling blocks on which Data Science thrive. I will like to know the correlation between this two fields. ThanksREAD MORE
One more thing which i missed in the article, that presence of outliers affects the distribution of the data. Let's examine what can happen to a data set with outliers. For the sample data set: 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4 We find the following: mean, median, mode, and standard deviation Mean = 2.58 Median = 2.5 Mode = 2 Standard Deviation = 1.08 If we add an outlier to the data set: 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 4, 400 The new values of our statistics are: Mean = 35.38 Median = 2.5 Mode = 2 Standard Deviation = 114.74 It can be seen that having outliers often has a significant effect on the mean and standard deviation and hence affecting the distribution. We must take steps to remove outliers from our data sets. One of the easiest way to handle this is log transformation.Hope this information will help you.READ MORE
Very nice explanation of a very common problem. Examples are given in such a way that any one can understand easily. Also remedies for under fitting and over fitting are given in a structured manner.keep it up.READ MORE
Emotions and Intelligence are a co-related phenomenon; therefore emotions must be taken into consideration for designing truly intelligent agent. Emotional intelligence has emerged as an important area of research in artificial intelligence covering wide range of real-life domains. In this article, we will focus on emotional intelligence research with an emphasis on areas such as Emotion detection, Emotional agents, Text emotion detection, Modeling artificial agent’s environments.READ MORE
As the volumes of data increase each day, organisations are begining on Data Science and Data Analytics to make sense of it. This article is a basic introduction to those new to the fieldREAD MORE
Good day!I would like to ask for some ideas related to Health Informatics that I can pursue for my capstone project for my graduate-level Health Informatics and Health Information Management. My ideal project will be data analytics, but open to any health informatics-related project ideas. I appreciate your input.Be safe and stay healthy!DennisREAD MORE
1. Sentiment Analysis2. Recognizing the face news3. Detection of the Parkinson disease4. Recognizing the speech emotions5. Age and Gender Detection6. OLA data analysis7. Credit Card Fraud Detection8. Recommended Movie9. Customer segmentation10. Classifying Breast CancerHere are the top 10 data science project which are listed one of my friend, want to know more about these visit here: https://hackr.io/blog/data-science-projectsREAD MORE
Researchers tested the tool with an AI-based neural network on videos of former U.S. President Barack Obama. The neural network spotted over 90% of lip syncs involving Obama himself.READ MORE
An Israeli start-up has launched its AI-powered food intelligence platform in the UK. The company – called Tastewise – says it can offer real-time industry insights on how consumers order, cook, and eat, to help brands with product innovation.READ MORE
It can play Go and underpins the future of driverless cars, but AI also help bolster your cyber defencesREAD MORE
In July, the Financial Times Future Forum think-tank convened a panel of experts to discuss the realities of AI — what it can and cannot do, and what it may mean for the future.READ MORE
Images generated by an algorithm are appearing increasingly in bot campaigns and online news outletsREAD MORE
Australia has an app that “fairly” allocates rights, responsibilities, and property in a divorce. The country’s authorities recommended using the tool instead of overloaded ships.READ MORE
The researchers at Centrum Wiskunde & Informatica (CWI) the Dutch national research centre for mathematics and computer science, collaborated with the IMEC/Holst Research Center from Eindhoven, Netherlands. They formulated a mathematical breakthrough that would assist in energy-efficient neural networks. The researchers have developed a deep learning algorithm known as Spiking Neural Networks that requires less frequency while communicating and involves minimum calculations for performing the task.READ MORE
AI (Artificial Intelligence) governance is about evaluating and monitoring algorithms for effectiveness, risk, bias and ROI (Return On Investment). But there is a problem: Often not enough attention is paid to this part of the AI process.READ MORE
But the graphs are in use previously too. So, What’s s new? The previously used individual graphs at training time were implicit, and the graph structure had to be hard-coded in the software. But with this new framework, the researchers can use WFSTs dynamically at the training time. Thus, the whole system can more efficiently learn and improve from the data.READ MORE
In its annual Internet of Things (IoT) survey, Internet of Things World found an overwhelming majority of (85 per cent) believe that security concerns remain a major obstacle to the roll out of IoT.READ MORE
Digital transformation is the process of moving operations and tools from a traditional offline environment to a digital one. Digital transformation with data specifically enhances business, delivers value through greater understanding and aligns digital and offline data. The first initiative that an organisation needs to take towards digitisation is by investing in wide data fluency skills.READ MORE
Deep learning is an imitation of actual human brain neurons and its functions.READ MORE
Focusing all the benefits of AI and ML, the utilisation of machine learning techniques in cybersecurity has been started only a few years ago and still at a niche stage. AI in cybersecurity can help in various ways, such as identifying malicious codes, self-training and other such. Here is a list of top eight machine learning tools, in alphabetical order for cybersecurity.READ MORE
A new review highlights the potential of machine learning--a subset of artificial intelligence -- in science education.READ MORE
The Data Science Foundation is committed to improving decision making. We believe that the use of data can improve decision making, but only if the social and environmental impact of decisions are evaluated alongside the knowledge and insight created though analytics. We work hard to help our members improve their decision making. To make good decisions today and to make better decisions tomorrow.
We help organisations new to evidence-based decision making; collect, process and analyse data. We help them appreciate the meaning hidden in their data so that they can understand more about the landscape in which they operate. We then help organisations who already have the expertise to collect data and create insight, to consider the moral implications of their actions. To think about the social and environmental impact of what the data might suggest is the best possible course of action.