Can Lack of Data Always Provide Valuable Insights?
Prashanth H Southekal and Matthew Joyce
Today, data – both structured and unstructured, is seen as the most valuable business asset to solve problems and improve productivity. An article in Forbes says every company today is a data company! However, we… Continue
Added by Prashanth Southekal, PhD on March 18, 2019 at 3:30am —
I spoke at the iot expo on AI and smart cities in London this week
Smart cities have been around for more than a decade
The overall numbers for Smart cities are promising
- 2018 over $81 billion was spent on Smart City initiatives and this number is expected…
Added by ajit jaokar on March 18, 2019 at 12:35am —
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.
Featured Resources and Technical… Continue
Added by Vincent Granville on March 17, 2019 at 7:30am —
Determining sample sizes is a challenging undertaking. For simplicity, I've limited this picture to the one of the most common testing situation: testing for differences in means. Some assumptions have been made (for example, normality and… Continue
Added by Stephanie Glen on March 17, 2019 at 7:00am —
Offline marketing is far from dead
The marketing communication industry has three main players: the brand, the agency and the media owner. The agency, who is typically the middle-man, has the most visibility in attribution and… Continue
Added by Pedro URIA RECIO on March 17, 2019 at 1:34am —
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on… Continue
Added by Vincent Granville on March 15, 2019 at 6:30am —
I propose a new word for data science for sparking new thinking. Signuology is defined as the study of sets of characteristic predictive signals contained within data in the form of combined features of the data that are characteristic of an observation of interest within the data.
The terms data mining and data structure imply rigid and discrete characteristics. A signal has more flexibility, borrowing from ideas contained in the superposition principle in physics. One can take the… Continue
Added by Steve Bowling on March 15, 2019 at 6:11am —
Key topics of this blog:
- Economies of scalehave historically given large enterprises unsurmountable market advantages through the exploitation of mass production, distribution and marketing.
- In Digital Transformation, “Economies of Learning”are more powerful than “Economies of Scale” because of the ability to learn and deploy those learnings within digital assets faster.
- Classic ERP “Big…
Added by Bill Schmarzo on March 15, 2019 at 5:04am —
As of now, chatbots are among the most trending technology for which the industry is excited to get in integrated. They get touted as the next rendition of applications, similar to an immense change in the correspondence business. Since Facebook has extended access to its messenger administration, it is enabling firms to achieve clients better… Continue
Added by Harikrishna on March 15, 2019 at 12:56am —
This is part 2 of a 3 part series: “How to make your mark on the world as a talented, socially conscious data scientist.”
You can find part 1 here: “Choose a domain which enables you to create… Continue
Added by Marshall Lincoln on March 14, 2019 at 10:30pm —
Over the last few years, blockchain has been one of the hottest areas of technology development across industries. It’s easy to see why. There seems to be no end to the myriad ways that forward-thinking businesses are finding. Furthermore, they are doing this to adapt the technology to suit a variety of use cases and applications. Much of the development, however, has come in one of two places. One is deep-pocket corporations… Continue
Added by Divya Singh on March 14, 2019 at 8:30pm —
With the growth of Data science in recent years, we have seen a growth in the development of the tools for it. R and Python have been steady languages used by people worldwide. But before R and Python, there was only one key player and it was MATLAB. MATLAB is still in usage in most of the academics areas and mostly all the researchers throughout the world use MATLAB.
In this blog, we will look at… Continue
Added by Divya Singh on March 14, 2019 at 12:00pm —
Here is our list of featured articles and technical resources posted since Monday. The picture is from the article flagged with a +.
Resources and Forum Questions
Added by Vincent Granville on March 14, 2019 at 9:30am —
This article was written by Krishna Kumar Mahto.
So, three days into SVM, I was 40% frustrated, 30% restless, 20% irritated and 100% inefficient in terms of getting my work done. I was stuck with the Maths part of Support Vector Machine. I went through a number of YouTube videos, a number of documents, PPTs and PDFs of lecture notes, but… Continue
Added by Andrea Manero-Bastin on March 14, 2019 at 6:30am —
Last month I had an honor to participate in data science project reviews for the new graduates of General Assembly's Data Science Immersive program. In the span of just three months of full-time studies and endless nights of homework Chicago campus students mastered Python programming skills, machine learning, and…
Added by Alex Blyakhman on March 14, 2019 at 5:15am —
Determining the number of clusters when performing unsupervised clustering is a tricky problem. Many data sets don't exhibit well separated clusters, and two human beings asked to visually tell the number of clusters by looking at a chart, are likely to provide two different answers. Sometimes clusters overlap with each other, and large clusters contain sub-clusters, making a decision not easy.
For instance, how many clusters do you see in the picture below? What is the optimum number… Continue
Added by Vincent Granville on March 13, 2019 at 2:30pm —
What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.
With the right tools, today’s average business user can become a Citizen Data Scientist, using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as… Continue
Added by Kartik Patel on March 13, 2019 at 3:00am —
The EM algorithm finds maximum-likelihood estimates for model parameters when you have incomplete data. The "E-Step" finds probabilities for the assignment of data points, based on a set of hypothesized probability… Continue
Added by Stephanie Glen on March 12, 2019 at 7:00pm —
We live in a world that is inundated with data. Data science and machine learning (ML) techniques have come to the rescue in helping enterprises analyze and make sense of these large volumes of data. Enterprises have hired data scientists — people who apply scientific methods to data to build mathematical software models — to generate insights or predictions that… Continue
Added by Abdul Matheen Raza on March 12, 2019 at 12:00pm —
A system is an entity that behaves based on the intrinsic characteristics of its components and the external forces that drive these elements to react as a result of their interaction with the environment.
When optimizing a system, three scenarios should be defined. The first is identifying all of its components, boundaries and the conditions acting upon it. The system intrinsically has a homeostatic point where it wants to exist and that may be not optimal for the… Continue
Added by Jose Bautista on March 12, 2019 at 9:00am —