Category Archives: Data Science News

Source We all are aware of AI and all the amazing things it is capable of. We have seen how it has helped us solve the most complex problems like they were no big thing and become more productive by reducing human error. However, AI also brings along the challenges of data privacy and security. InContinue reading “How AI is Affecting the VPN Industry”

No Bias Labeled Data — the New Bottleneck in Machine Learning The Performance of an AI System Depends More on the Training Data Than the Code Over the last few years, there has been a burst of excitement for AI-based applications through businesses, governments, and the academic community. For example, computer vision and natural language processing (NLP) where outputContinue reading “No Bias Labeled Datathe New Bottleneck in Machine Learning”

During the study of Data Science, I met a batch of new algorithms and libraries useful for data analysis and predictions. All of them have their cons and pros. It is not a surprise. But only one algorithm has a reputation as lazy and greedy from the first word. You can put in this definitionContinue reading “How I meet the KNN algorithm.”

EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code… and it might even be fun! OriginallyContinue reading “Powerful Exploratory Data Analysis in just two lines of code”

Data Quality Monitor implements novel statistical methods for anomaly detection and quality management in large data infrastructures. Originally from KDnuggets https://ift.tt/2Mdbh25 source https://365datascience.weebly.com/the-best-data-science-blog-2020/inside-the-architecture-powering-data-quality-management-at-uber

New KDnuggets Cartoon examines the problems of Data Scientists vs Data Engineers. Originally from KDnuggets https://ift.tt/3pHLBbr source https://365datascience.weebly.com/the-best-data-science-blog-2020/cartoon-data-scientist-vs-data-engineer

Research shows that people skills are becoming more important with the rise of AI. A great way to boost these skills is by reading the new book: People Skills for Analytical Thinkers. Originally from KDnuggets https://ift.tt/3sdWwv9 source https://365datascience.weebly.com/the-best-data-science-blog-2020/people-skills-for-analytical-thinkers

This tutorial discusses the confusion matrix, and how the precision, recall and accuracy are calculated, and how they relate to evaluating deep learning models. Originally from KDnuggets https://ift.tt/2ZKmieF source https://365datascience.weebly.com/the-best-data-science-blog-2020/evaluating-deep-learning-models-the-confusion-matrix-accuracy-precision-and-recall

Photo by Donald Giannatti on Unsplash “Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.” –Josh Wills, Director of Data Engineering at Slack We stand in midst of a deluge of data today. Starting from the smartphone in your palm to the smart refrigerator atContinue reading “A Comprehensive Roadmap for An Aspiring Data Scientist in 2021”

Photo by Mike van Schoonderwalt from Pexels Let’s face it, even before we were properly exposed to data science we had probably heard both of these terms: overfitting and underfitting. The reason these two terms shall be regarded as the guiding philosophy of machine learning is that every machine learning model in existence conforms to theContinue reading “Overfitting vs Underfitting: The Guiding Philosophy of Machine Learning”