All you need to query account balances, transactions, token transfers, and much more.
Motivation
Founded back in 2017 by Justin Sun and the TRON Foundation, today TRON is one of the most popular blockchain projects out there. Its growing popularity is mainly driven by its speed and low transaction costs, allowing for the development of robust decentralised applications (dApps), especially online games. As a result, the project has recently gained much traction and several high-profile partnerships, including joint ventures with the likes of BitTorrent, Samsung, Huawei, Opera, etc. In February 2021, the market capitalisation of Tronix (TRX), the native currency of TRON, exceeded $4.2B.
Model Interpretability
Here is what you tell them.
Setting the scene
You are a Data Scientist working for a commercial company. You spent weeks, or maybe even months, developing this deep learning-based model that accurately predicts an outcome of great interest to your business. You proudly presented the results to your stakeholders. Quite annoyingly, though, they did not pay much attention to that cutting-edge approach you used to build the model. Instead of focusing on how powerful the model was, they started asking lots of questions on why some of its predictions looked the way they did. Your colleagues also felt that some of the critical predictors were missing. They could…
Estimates of the COVID-19 excess deaths obtained in this study make Belarus comparable to the UK, Italy, USA and other countries most affected by the virus.
Background
The Belarus Ministry of Health has not yet published any mortality data for 2020 on their official website. However, as found by journalists of a local online news outlet “Nasha Niva”, the Ministry did pass such monthly data to the United Nations Organisation, which made them available at the UNdata portal. Based on that data, journalists concluded that the cumulative excess death toll during the COVID-19 outbreak in April — June 2020 made up…
…and now help me in my day-to-day work
I started my career as an academic researcher in the areas of Ecology and Invasion Biology. That involved lots of fieldwork and lab experiments, followed by statistical analyses of the collected data and publishing in peer-reviewed journals. In addition, I taught several data analysis-heavy courses to university undergrads and Master students, including Biostatistics, Population Ecology, and Ecological Modeling.
All of that experience became extremely useful when I decided to leave academia and apply my data analysis skills to solving business problems. Believe it or not, my decision at the time was triggered by the famous article in Harvard Business Review…
“Requirements rarely lie on the surface”
The majority of Data Science projects fail. I will not even provide any references in support of this statement — the Internet is full of examples. The reasons for the high failure rate are many and varied. However, as surprising as this may sound, one of the main reasons is the lack of clearly defined project goal(s) and the associated requirements.
Problem understanding and requirements gathering make up an initial phase in pretty much any project management framework, including the widely used “Cross-Industry Standard Process for Data Mining” (CRISP-DM). This implies that the project goals and requirements are already there…
Opinion
Focus on automated decision making instead
Open any large job board and search for “Data Scientist” positions. Many of the returned job specs will contain a requirement to produce data-driven insights that can be used to optimise business processes or products of the hiring organisation. In this context, “insight” is defined as a novel piece of useful information that has been extracted from data using Statistics or Machine Learning techniques. Here are just a few excerpts from the job ads found on LinkedIn:
- “Perform hands-on data analysis and modelling with very large data sets to develop insights into different aspects of our business.”
- “You will define…
Use This Instead
Information contained in User-Agent strings can be efficiently represented using low-dimensional embeddings, and then employed in downstream Machine Learning tasks.
What on Earth are User-Agent strings?
When a user interacts with a website, the browser sends HTTP requests to the server to fetch the required content, submit data, or perform other actions. Such requests typically contain several headers, i.e. character key-value pairs that specify parameters of a given request. A User-Agent string (referred to as “UAS” below) is an HTTP request header that describes the software acting on the user’s behalf (Figure 1).
As of September 2020, Georgia has lost 4.6M international tourists and $339M worth of foreign card transactions due to the COVID-19 pandemic.
Until recently, tourism has been a fast-growing industry in Georgia
Soon after it gained independence from the Soviet Union, Georgia has demonstrated significant economic achievements. Today, it is one of the least corrupt nations in the Black Sea region and a highly ranked country for its ease of doing business. Georgia also has a rich history, unique winemaking tradition, incredible cuisine, and picturesque landscapes, making it one of the most attractive destinations for tourists and business people from around the globe.
“Movies are now no longer freestanding IP; they are one piece in a marketing assault” (Alpert & Jacobs 2004)
Popular among players, slots dominate the game content of any real-money online casino. It is common for online casino operators to offer their players hundreds and even thousands of slot titles to choose from. This diversity, however, makes it increasingly more difficult for casinos to differentiate themselves on the crowded market. One way to tackle this problem is to offer games that possess unique yet recognisable themes, such as games based on popular movies.
Sergey Mastitsky
Data Science consultant with multiple years of experience across academic and industrial sectors. Author of several books on data analysis and visualisation.
