The Role of Data Science in Big Data Analytics
Data Science
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 Data Science Projects 2020
Data Science
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
Data Scientist's Role & Ethical Challenge
Data Science
The job of the data scientist and the ethical challenges they face
What ethical issues are involved with Big Data? But, overexposed or not, the Big Data revolution raises a bunch of ethical issues related to privacy, confidentiality, transparency and identity.
The art of Learning to Learn by using the Power of Meta-Learning in AI
Data Science
Machine learning is a fast-paced area and many types of research are ongoing. One of the fastest growths can be seen in the area of Meta-learning. As it is becoming more popular and more meta-learning techniques are being developed, it is important to understand this area of data science. Meta-learning caught my attention somewhere back in 2018
Very nice article Abhishek. Particularly, Three main steps to create a meta-learning model are too good.
Expectation-Maximization algorithm
Data Science
Given a set of incomplete data, consider a set of starting parameters. Expectation step (E – step): Using the observed available data of the dataset, estimate (guess) the values of the missing data. Maximization step (M – step): Complete data generated after the expectation (E) step is used in order to update the parameters. Repeat step 2 and step 3 until convergence.
The Expectation-Maximization (EM) algorithm is a way to find maximum-likelihood estimates for model parameters when your data is incomplete, has missing data points, or has unobserved (hidden) latent variables. It is an iterative way to approximate the maximum likelihood function.
Pivotal Data Labs Helps Predict Viewer Behavior and Build a Better TV Show
Data Science
Media companies have long been interested in viewer habits and preferences. In the past, they were forced to rely on traditional sources of data to determine this information, which would then be used to help formulate the next series of TV shows, many of which would ultimately “flop.” However, the rise of unstructured data has given media companies and TV executives the means to dig deeper and make better decisions.
In the past, they were forced to rely on traditional sources of data to determine this information, - Quite a point
Data Science Allows Fashion Industry to Gain a More Complete Understanding of Consumers
Data Science
The fashion industry is pretty visible in terms of high-profile events held in cities like New York or Milan. Fashion designers drape models with their latest creations, and then those models stroll down the catwalk while photographers turn night to noon with flashes. However, while that might be the public image of the industry, fashion companies face significant challenges. Rather than leading consumers with new designs and styles, these companies still must understand their audience, what drives them, and what consumer behaviors affect their success. Data science is being used to do just that.
Data Science Allows Fashion Industry to Gain a More Complete Understanding of Consumers article nicely explained.
Crisis Text Line Gets Help through Data Science Company Pivotal to Save the Lives of At Risk Teens
Data Science
While millions of people are at risk of committing suicide, teens are often the most in distress. A number of solutions have been created to reach at-risk teens and help prevent them from taking their own lives. One of these is Crisis Text Line. However, the organization found that it required assistance in measuring interaction value and creating predictive models to help create positive outcomes in the future.
A number of solutions have been created to reach at-risk teens and help prevent them from taking their own lives. - Quite a point
Silicon Valley Data Science Helps Health Integrated Plot a Course for the Future
Data Science
For any business, plotting a course into the future can be immensely difficult. However, for a health care provider with thousands of patients, doctors, nurses and support staff, that issue becomes infinitely more complex. Silicon Valley Data Science was able to help Health Integrated chart such a course to create a “roadmap for technical capability development designed to address those needs tied to the most pressing and valuable business aspirations.”
roadmap for technical capability development designed to address those needs tied to the most pressing and valuable business aspirations. - Quite apoint
Mathematical Biologist to Deliveroo Data Scientist
Data Science
Why Science to Data Science? Read about Jonny’s journey from mathematical biologist to data scientist, what a typical day looks like, and his experience after a year in the role.
Why Science to Data Science? - a questions a answer a possible solution to find.. A very clearly written