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
Handling Imbalance class
Imbalance Class is one of the most discussed problems in data science. This article will provide examples of some of the commonly used techniques to deal with imbalance class in data set problems Read more
How Python Helps To Protect Data from Hackers Attacks
In this article, we will tell you 7 Facts that you don’t already know about Python. With little effort, a hacker can create a script of less than 100 lines that creates a persistent weakness. So, that even if you kill the process, it will start itself back up, establish a backdoor, obfuscate communications both internally and with external servers. Read more
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.
The Rise in Artificial Intelligence Makes Emotional Intelligence More Important
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.
Dear team, I am working on a research based on content-based package selection in the telecom industry. So I want to get a data set based on customer usage of their package. I mean internet usage, voice usage etc. Can you please give me a support. Anyone have that type of a data set, can you please share with me.READ 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
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
Digital forensics refers to the way toward recouping information from computerized gadgets, from PC hard drives to cell phones. This movement is frequently connected with criminal or common investigations.READ MORE
Researchers show how incorporating the symmetries of physics theories into machine learning and artificial intelligence architectures can provide much faster algorithms for theoretical physics.READ MORE
Researchers at the University of California San Diego School of Medicine used artificial intelligence technologies to analyze natural language patterns (NLP) to discern degrees of loneliness in older adults.READ MORE
A machine-learning algorithm that can detect subtle signs of osteoarthritis and patients could one day be treated with preventative drugs rather than undergoing joint replacement surgery.READ MORE
How should people make decisions when the outcomes of their choices are uncertain, and the uncertainty is described by probability theory?READ MORE
The prediction marks a significant revision of previous estimations of the so-called technological singularity, when machine intelligence surpasses human intelligence and accelerates at an incomprehensible rate.READ MORE
European Bishops urge the European Union to embrace a human-centric approach in its continued deliberations on the use of Artificial Intelligence.READ MORE
Over 1,800 abstracts spanning more than 50 Warfighter related topic areas were accepted for oral or poster presentation at the 2020 Military Health System Research Symposium. Although the meeting was cancelled due to COVID-19, the accepted abstracts having author permission are now available on-line through the homepage of the MHSRS website. VISIMO's abstract (ID: MHSRS-20-01758) titled "Integration of Wearables Data and Subject Matter Expertise in a Military Risk Reduction Setting" was accepted to the "Wearable Sensors for Human Monitoring" category and was to be presented by Dr. Robert Powers (PhD, Carnegie Mellon University) and co-authored by VISIMO employees Dr. Robert Powers, PhD., Mr. Constantine Mintas, JD., Mr. Alexander Heit, MPA,, and Mr. Jacob Leisey-Bartsch, MA.READ MORE
The European Defence Agency has set its sights on developing artificial intelligence (AI) to strengthen the EU’s defence forces in the near future. This is in line with calls from Germany in May to create a European Defence Union within the next ten years.READ MORE
VISIMO, a leading provider of artificial intelligence and machine learning solutions, has been selected by the Autonomy Research Collaboration Network (ARCNet) and the Air Force Research Lab (AFRL) to deliver Project Coeus, a joint effort for the U.S. Army Futures Command Artificial Intelligence Task Force (AFC AITF) and the Joint Test Resource Management Center (TRMC). Coeus will serve as the Department of Defense’s (DoD’s) state-of-the-art collaboration tool, a secure “Open Community Data Science Platform” to support autonomy and artificial intelligence (AI) requirements, significantly increasing the effectiveness of researchers and data science technicians within the DoD.READ MORE
Data science has been no more a luxury for companies — this COVID-19 pandemic has forced companies to rely on data-driven strategies, and thus made data science a key aspect in running businesses.READ MORE
As an emerging technology, AI faces and will continue to face its fair share of challenges. On the one hand, consumers remain wary about adopting new tech.READ MORE
Supervised algorithms require lots of data, and often result in shaky predictions. Is it time for the next stage of AI?READ MORE
DataRobot, the automated machine learning software vendor, continued its string of acquisitions this week with a deal to buy Boston Consulting Group’s AI technology platform.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.