Category: Featured

Feed: Featured Blog Posts - Data Science Central. Author: Robert R. Tucci. I just uploaded a new chapter to my github proto-book "Bayesuvius". This chapter deals with Reinforcement Learning (RL) done right, i.e., with Bayesian Networks :) My chapter is heavily based on the excellent course notes for CS 285 taught at UC Berkeley by Prof. Sergey Levine. All I did was to translate some of those lectures into B net lingo. During a recent conversation that I had on LinkedIn with some very smart Machine Learning experts, the experts opined that the fields of RL and B nets did ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Kate Shao. With the continuous development of network technology and the ever-expanding scale of e-commerce, the number and variety of goods grow rapidly and users need to spend a lot of time to find the goods they want to buy. This is information overload. To solve this problem, the recommendation system came into being. The recommendation system is a subset of the Information Filtering System, which can be used in a range of areas such as movies, music, e-commerce, and Feed stream recommendations. The recommendation system discovers the user’s personalized needs and interests by analyzing ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Sandipan Dey. This is the 2nd part of the article on a few applications of Fourier Series in solving differential equations. All the problems are taken from the edx Course: MITx - 18.03Fx: Differential Equations Fourier Series and Partial Differential Equations. The article will be posted in two parts (two separate blongs) We shall see how to solve the following ODEs / PDEs using Fourier series: Solve the PDE for Heat / Diffusion using Neumann / Dirichlet boundary conditions Solve Wave equation (PDE). Remove noise from an audio file with Fourier transform. Heat / Diffusion Equation The ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Subin George. Over a period, large organizations have been transformed into disintegrated silos that has grown to be a major impediment to respond to changing market demands with agility. Organizational silos have led to innumerous disconnected policies, systems, processes, standards, teams. In order to sustain in this digital era, it’s imperative for organizations to take a top down enterprise value chain view to continually evaluate its ability to adapt (as well as compete) to changing market demands->change business models and/or objectives->create or optimize processes->design or enhance systems->manage and govern data. Often ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link. Announcement Our supply chain superheroes are needed now more than ever - Upcoming webinar Selected Data Science Programs from Top Universities Featured Resources and Technical Contributions Fourier Series and Differential Equations with applications in R - Part 1 Math vs. Statistics in One Picture 23 sources of data bias for machine learning and deep learning New ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Jeefri A. Moka. What is a commodity? Commodity are basic raw materials with certain standards that are used with other goods, commodity are often the basis of the production of various finished goods or services and then referred to as commodities (something made based on commodity). Some examples of commodity are seen from their types: metal (gold, silver, platinum, and copper); energy (crude oil and natural gas); livestock and agriculture (beef, mutton, rice, wheat, corn, soybeans, chocolate, coffee, sugar); and others. Data like a commodity There are several related terms about ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: saurabh ajmera. Image by Arek Socha from Pixabay Profit analysis is an integral part of analysis drills, which are conducted at regular frequency. Both finance and marketing departments are equally engaged in this activity — though both have a different approach to it. Variance analysis is a powerful tool, being extensively used by finance departments — but even for marketing, it holds no lesser value. With a traditional contributor analysis, already the executive presentations of marketing look a plenty, but addition of variance analysis will definitely be favoring. As the name suggests, this analysis ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Alex Castrounis. Download chapter 1 for FREE from my book, AI for People and Business: A Framework for Better Human Experiences and Business Success, published by O'Reilly Media. You can also grab a copy on Amazon. Thanks and I hope you enjoy!  Alex Castrounis Book Testimonials “A must read for business executives and managers interested in learning about AI and unlocking its benefits. Alex Castrounis has simplified complex topics so that anyone can begin to leverage AI within their organization.” - Dan Park, GM & Director, Uber “Alex Castrounis has been at the ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: William Vorhies. Summary:  Bias in modeling has long been a public concern that is now amplified and focused on the disparate treatment models may cause for African Americans.  Defining and correcting the bias presents difficult issues for data scientists that need to be carefully thought through before reaching conclusions. The hue and cry over potential bias in modeling is not new news.  We first wrote about it in 2018 when there was broad based concern over individuals being impacted unfairly by the results of our models.  The academic field of ethical ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: ajit jaokar. In the paper A survey on bias and fairness in machine learning.- the authors outline 23 types of bias in data for machinelearning. The source is good – so below is an actual representation because I found it useful as it is full paper link below 1) Historical Bias. Historical bias is the already existing bias and socio-technical issues in the world and can seep into from the data generation process even given a perfect sampling and feature selection. An example of this type of bias can be found in a ... Read More