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.
Data Science and Econometrics
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. Thanks
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”.
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.
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.
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.
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.
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
Looking for Health Informatics & Data Analytics Project Idea
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!Dennis
Looking for Data Science Projects 2020
Hello All, Can anyone know latest data science project name in 2020? I want to learn about all the project information during this lockdown.
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-projects
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.
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.
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.