Three Ways Data Scientists are Fighting COVID-19
Data scientists in academia, non-profits, and the government have come together to track and respond to the economic & humanitarian impacts of the coronavirus. Read more
5 Key Challenges In Today’s Era of Big Data
We are currently in the middle of an AI renaissance, driven by big data and breakthroughs in machine learning and deep learning. These breakthroughs offer opportunities and challenges to companies depending on the speed at which they adapt to these changes. Read more
Linear Discriminant Analysis
Linear Discriminant Analysis (LDA) is an effective classification method, and it is simple and easy to understand. It is useful when the number of input features increases to the point where the predictive modeling function of a model becomes too difficult for the model to function. This is more commonly called the curse of dimensionality. Read more
PageRank Algorithm - Identify dominant nodes
An introduction to the PageRank algorithm. While clusters expose regions with highly localized interactions, dominant nodes in which clusters form may govern such interactions. We use the ranking to identify these dominant nodes. Read more
The Role of Data Science in Big Data Analytics
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 field Read more
Louvain Algorithm - Identifying Communities within Networks
We could take a more structured approach and develop our understanding of social groups on a much larger scale. This would require the use of a methodology to investigate how individuals respond to one another, such as quantifying an individual’s influence and their impact on group dynamics. Read more
Getting Started with Seaborn : Basics Tutorial
Python has many great visualization tools. But, one that really stands out is Seaborn. It is a powerful library used by many Data Scientists in order to work with data. This article will run through some basic & most simplest steps in order to give you hands on experience with Seaborn. Read more
k-Nearest Neighbor (k-NN) for Machine Learning
When it comes to classification problems relating to reducing attrition rates, one algorithm that always comes handy is k-Nearest Neighbors (k-NN). Ever heard of the old saying that's "Birds of a feather flock together", k-NN can be said to be a representation of this quote. In this article we will try to understand more about this algorithm. Read more
Data.world and John Snow Labs partner to make 2,200 current, linked, and expert-curated healthcare datasets available to COVID-19 researchers & data scientists
Data.world, the cloud-native data catalog, and healthcare AI & NLP provider John Snow Labs are partnering to fight the global COVID-19 pandemic by sharing data and software for virus researchers. Read more
Florida Data Scientist Fired for Refusing to Manipulate Data
It has been widely reported that a data scientist in Florida was fired for refusing to manipulate the data being presented on the COVID-19 dashboard she had created. This incident raises many issues and it is appropriate that the Data Science Foundation expresses an opinion. Read more
What have the changes made to primary and secondary assessment frameworks done to the ‘London effect’ in school performance?
This paper examines whether the so-called ‘London effect’, in which London’s schools improved rapidly and outperformed the rest of England on key performance measures between 2003 and 2013, has persisted through the high levels of change that have continued to characterise the school system in England since 2013.
The transformational shift in educational outcomes in London 2003 to 2013: the contribution of local authorities
The paper explores the transformational shift in educational outcomes in London between 2003 and 2013. London’s schools have improved rapidly over the past decade, with primary and secondary schools now out-performing the rest of the country, at Key Stages 2 and 4, respectively. Improvements in many London boroughs have been staggering.
Open Source Solutions for Building Your Own Storage Area Network and Network Attached Storage
Enterprise NAS and SAN solutions are generally closed systems offered by traditional vendors like EMC and NetApp with a very large price tag, so many businesses are looking at Open Source solutions to meet their needs.
Understanding Decision Trees with Python
Decision Trees, the popular and time-tested method of applying logic to complex problems, where the variables are many and the options specific and dependent, have an important role to play within Machine Learning. We will dedicate this paper to understanding why this reasonably humble technique has become such an important tool for data scientists.
An Overview of Autopsy: Open Source Digital Forensic Platform
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.
Statistical Testing - Understanding Which Testing Methods to Use
Data Science, Machine Learning, Artificial Intelligence, Deep Learning - You need to learn the basics before you become a good Data Scientist. Math and Statistics are the building blocks of Algorithms for Machine Learning. Knowing the techniques behind different Machine Learning Algorithms is fundamental to knowing how and when to use them. In this paper, we will look at statistics as a concept. What are the different tests and most important, ‘When to use which test?’. So let us begin by learning more about statistics.
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
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
Very good informative and knowledgeable article for the learners to learn and get the ideas of the working of the different types of setup which are been used over here.Very nice work.READ MORE
How does Walmart use big data? By analyzing customer preferences and shopping patterns, Walmart can optimize how to stock shelves and display merchandise. Big data also provides insight into new items, discontinued products and which brands to carry, the blog said.READ MORE
Machine Learning Algorithms Linear Regression. To understand the working functionality of this algorithm, imagine how you would arrange random logs of wood in increasing order of their weight. ... Logistic Regression. ... Decision Tree. ... SVM (Support Vector Machine) ... Naive Bayes. ... KNN (K- Nearest Neighbors) ... K-Means. ... Random Forest.READ MORE
Go to the admin section in your Google Analytics (the gear icon at the bottom left corner), Under the View column (master view), click the button “Filters” (don’t click on “All filters“ in the Account column): Click the red button “+Add Filter” (if you don’t see it or you can only apply/remove already created filters, then you don’t have edit permissions at the account level. Ask your admin to create them or give you the permissions.): Then follow the specific configuration for each of the filters.READ MORE
Here are five strategies for promoting your personal brand internally: Get your boss to help with visibility. ... Join (or start) an ERG. ... Volunteer for a cross-departmental activity. ... Promote your company's brand. ... Leave your desk.READ MORE
Can you have too much data? But the truth is you can have too much data. In fact, sometimes having more data can actually make things worse, leading us to act in ways that can be counterproductive. Sometimes having more data can actually make things worse, leading us to act in ways that can be counterproductive.READ MORE
Very nice article Abhishek. Particularly, Three main steps to create a meta-learning model are too good.READ MORE
This was good information given by the author. Kindly post these type of information for our updates.and please post webinar also.READ MORE
The U.S. economy may have hit its low point in the coronavirus crash but the rebound so far remains tepid, according to both broad indexes of activity and higher frequency counts of cellphone data and employee time information.READ MORE
Researchers demonstrated a technique that converts malware binary form into grayscale images, which are scanned by an image pattern recognition algorithm.READ MORE
Data scientists are much in demand. But there’s a gender gap.READ MORE
Machine-learning models trained on normal behavior are showing cracks —forcing humans to step in to set them straight.READ MORE
This research measures the future impact of COVID-19 on the global Big Data Analytics (BDA) market. The embedded ecosystem has led to a hyper-connected world and the growth of the Internet of Things (IoT). Thanks to ubiquitous networks, IoT has connected all manner of endpoints and unveiled a treasure trove of data.READ MORE
The world has not known, in living memory, a pandemic on the scale of what we are experiencing with COVID-19.READ MORE
AI has become a key weapon in tracking and tracing cases during this pandemic. Deploying those technologies has sometimes meant balancing the need to conquer the virus with the conflicting need to protect individual privacy.READ MORE
An alternative approach for policy makers to consider adding in their mix for battling Covid-19 is based on the technology of personalized prediction with AIREAD MORE
Big data analytics techniques are well-suited for tracking and controlling the spread of COVID-19 around the world.READ MORE
These articles explain some of the latest applications for predictive analytics and machine learning AIREAD MORE
Imperial researchers and Coursera have partnered to offer a free Massively Open Online Course explaining the science behind coronavirus.READ MORE
Find out about the ways in which Health Data Research UK, as the national institute for health data science for England, Wales, Scotland and Northern Ireland, is championing the use of health data to respond to COVID-19.READ MORE
The first and only fully-curated power list of the most influential data and analytics practitioners in UK organisations.READ MORE
An over-regulation of AI could hand technical superiority to countries like China and Russia, leading to a ripple effect on America’s GDP and even threatening national security.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.