Tokenomics is the economy of this new world. This is a no-holds-barred, in-depth exploration of the way in which we can participate in the blockchain economy.
The following is an excerpt from the book, Tokenomics by Thomas Power and Sean Au and published by Packt.
One of the biggest challenges of…Continue
Added by Packt Publishing on December 12, 2018 at 4:06am — No Comments
It’s been said that Data Scientist is the “sexiest job title of the 21st century.” This is because of one main reason that there is a humongous amount of data available as we are producing data at a rate as never before. With the dramatic access to data, there are sophisticated algorithms present such as Decision trees, Random Forests etc. When there is a humongous amount of data available, the most intricate part is to select the correct algorithm to solve the problem.…Continue
Added by Divya Singh on December 11, 2018 at 4:00am — No Comments
Who wants to hear a story about data?!
Understandably, not a lot of people would raise their hands to an intro like that. For me, however, data has sculpted my career path and led to many exciting opportunities over the life of my profession. It hasn't been easy -- I think any entrepreneur would tell you the same and surely the content and media attention around self-starting individuals would concur. But I'm not here to tell you about the hardships of…Continue
Added by John E Sukup on December 11, 2018 at 3:00am — No Comments
The opportunity to watch and coach the University of San Francisco (USF) students during our annual Hackathon with our friends at Good Dataprobably taught me as much as it taught the students. The lessons learned I’ll share here will not only benefit future classes, but my customers. It also gives me an opportunity to make special mention of one Hackathon team that really delivered the goods!…Continue
Added by Bill Schmarzo on December 10, 2018 at 5:23pm — No Comments
In 1963 Benoit Mandelbrot published an article called “The Variation of Certain Speculative Prices.” It is a response to the forming theory that would become Modern Portfolio Theory. Oversimplified, Mandelbrot’s argument could be summarized as “if this is your theory, then this cannot be your data, and this is your data.” This issue has haunted models such as Black-Scholes, the CAPM, the APT and Fama-French. None of them have survived validation tests. Indeed, a good argument can be…Continue
Added by David Harris on December 10, 2018 at 2:00pm — No Comments
Summary: We’re rapidly approaching the point where AI will be so pervasive that it’s inevitable that someone will be injured or killed. If you thought this was covered by simple product defect warranties it’s not at all that clear. Here’s what we need to start thinking about.
“What you see is what you buy”
It is believed that 95% of the purchase decisions happen in the subconscious (let’s call it the reptile…Continue
Added by Ayush Srivastava on December 10, 2018 at 12:50am — No Comments
Added by Vincent Granville on December 9, 2018 at 3:30pm — No Comments
Updated on Dec 12, 2018. An error was fixed when g(x) is not equal to x, and a new section "Generalization" was added. A link to a large collections of intriguing integrals was added at the bottom, in the "Related Problems" section.
Below are a few integrals that you won't find in textbooks. Solving them is a good exercise for college students with some advanced calculus training. We provide the solution, as well as a general framework to compute many similar integrals. Maybe…Continue
Machine learning is the branch of computer science and a subfield of Artificial Intelligence that utilizes past data to learn from and use its knowledge to make future decisions. Machine learning is at the intersection of computer science, engineering, and statistics. The goal of machine learning is to generalize a detectable pattern or to create an unknown rule from given examples.
Machine learning is broadly classified into three categories but nonetheless, based on the…
Added by Malvika Mathur on December 8, 2018 at 11:00pm — No Comments
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, outliers, regression, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting,…Continue
Added by Vincent Granville on December 8, 2018 at 9:00am — No Comments
The rise in Machine Learning, Deep Learning and Artificial Intelligence technologies seems to breaking all barriers. All these technologies have the potential to spur innovation everywhere in the world. When it comes to deep learning, the technological advancement seem to be very uplifting. They have the power to help the companies perform better and more quickly. But, at the same time, there is certain amount of confusion surrounding these technologies as well.…Continue
Added by Samual Alister on December 7, 2018 at 5:00am — No Comments
Think back to the last time you texted a chatbot. Whether it was a concierge, a customer support assistant, or an AI…Continue
Added by Ashok Narendranath on December 6, 2018 at 9:00pm — No Comments
Optimized Promotion Placement
The promotions page on any website during an offer period, may it be Thanksgiving, Cyber Monday or even Ester has tons of products scattered across the page. There could be multiple business rules governing the position of the products. Couple of…Continue
Added by saurabh ajmera on December 6, 2018 at 11:30am — No Comments
Here is our selection of featured articles and resources posted since Monday:
Upcoming DSC Webinar
Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (graphical and quantitative) to better understand data. It is easy to get lost in the visualizations of EDA and to also lose track of the purpose of EDA. EDA aims to make the downstream analysis easier.…Continue
Added by ajit jaokar on December 6, 2018 at 5:49am — No Comments
My writing engagement at Data Science Central came up unexpectedly. Back in August 2018, I stumbled upon an excellent write-up on Data Science Central. The author, Bill Vorhies, shared his thoughts on career transitioning toward data science. I wrote him an email, complimenting him on his blog post, and I dropped a few lines about my own transition. Here's his response:
"Congratulations on your remarkable journey. Perhaps you’d like to write one or more articles…Continue
In this article, I hope to inspire you to start exploring satellite imagery datasets. Recently, this technology has gained huge momentum, and we are finding that new possibilities arise when we use satellite image analysis. Satellite data changes the game because it allows us to gather new information that is not readily available to businesses.
Added by Michał Frącek on December 6, 2018 at 2:30am — No Comments
With the introduction of big data, the need for its storage increased gradually. Companies were focussing on building solutions and frameworks to store as much data as possible. When this problem is addressed by big names such as Hadoop, companies shifted their focus on data processing. Here, the popular term that everyone might have heard once is “data science.” Undoubtedly, data science is considered as the future of AI…Continue
Added by Ritesh Patil on December 6, 2018 at 2:00am — No Comments
The goal of both logical and physical architecture specifications is to define and document the logical and physical components of a system, respectively, in order to provide clarity around how those component elements relate to one another. The artifacts resulting from either effort could be text documentation, or diagrams, and both have their own advantages and drawbacks.
This is an extract is taken from …Continue
Added by Packt Publishing on December 6, 2018 at 12:47am — No Comments