Having spent the better part of the last decade helping organisations in the U.S. and the U.K. use data to drive profit, efficiency, and performance improvements, I thought it would be helpful to jot down best practices for organizations that are looking to get the most value out of their enterprise-level financial and operational data sets.
Every organisation entering the roaring 20s knows that they must use their data as a strategic differentiator to gain a competitive advantage and…Continue
Added by Fahad Zaidi on January 19, 2020 at 6:00am — No Comments
Data Science methods and techniques allow new approaching the solution of complex tasks in terms of mathematics, and statistics for the various aspects and areas of our life, work, and business. Therefore, this makes it possible to produce the most unobvious…Continue
Added by Igor Bobriakov on January 16, 2020 at 10:30am — No Comments
Software is always not only a set of instructions but also a context that manages, interacts and executes these instructions. At the start of developing, the engineer configures a dev environment. He can continue to change it in all stages of development. The problem appears when…Continue
Added by Igor Bobriakov on January 14, 2020 at 6:00pm — No Comments
One of the main requirements for modern information systems is the high data processing rate. Among the solutions to solve this problem the popular one is to use high-performance databases. This article will review and compare two popular databases in performance terms:…Continue
Added by Igor Bobriakov on January 10, 2020 at 12:12am — No Comments
25 Experts have compiled this list of Best Python for Machine Learning Course, Tutorial, Training, Class, and Certification available online for 2020. It includes both paid and free resources to help you learn Python for Machine Learning and these courses are suitable for beginners, intermediate learners as well as experts.
If you are interested in getting started with the field…Continue
Added by Digital Defynd on January 3, 2020 at 9:30pm — No Comments
As a data scientist in an organization you frequently find yourself in a couple of situations:
Added by Mab Alam on December 27, 2019 at 8:00pm — No Comments
In the abundance of…Continue
Added by Max Ved on December 23, 2019 at 2:31pm — No Comments
Today, one of the most popular tasks in Data Science is processing information presented in the text form. Exactly this is text representation in the form of mathematical equations, formulas, paradigms, patterns in order to understand the text semantics (content) for its further…Continue
Production sphere embraces a wide range of processes related to all branches and stages of creating material goods. In addition, these material goods may be of different values and even have rather contrasting goals.
Added by Igor Bobriakov on December 18, 2019 at 8:30am — No Comments
Data science and analytics are growing in their popularity and range of applications in the modern world. Data science deals with answering questions and uncovering hidden insights, while analytics is rather concentrated on the processing itself and conducting of statistical…Continue
Added by Igor Bobriakov on December 18, 2019 at 8:00am — No Comments
H2O is a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks. The dataset we are using is the Bank Marketing Dataset. Here we need to train a model which will be able to predict if the client of the bank opens…Continue
Added by Igor Bobriakov on December 16, 2019 at 8:00am — No Comments
The history of F1 motor racing and the use of telemetry as a way to monitor car setup and performance dates back to the 80s. The first electronic systems were installed onboard the car, collected information for only one lap and the data were then downloaded when the car was back in the garage. The explosion of computing capabilities, in the 90s, contributed to the growth of intelligent data usage in the F1 and the…Continue
Added by Valeria on December 13, 2019 at 1:00am — No Comments
Walking by the hottest IT streets in these days means you've likely heard about achieving Streaming Machine Learning, i.e. moving AI towards streaming scenario and exploiting the real-time capabilities along with new Artificial Intelligence techniques. Moreover, you will also notice the lack of research related to this topic, despite the growing interest in it.
If we try to investigate it a little bit deeper then, we realize that…Continue
Added by Valeria on December 10, 2019 at 7:30am — No Comments
Big Data is probably one of the most misused words of the last decade. It was widely promoted, discussed, and spread around by business managers, technical experts, and experienced academics. Slogans like “Data is the new oil” were widely accepted as unquestionable truth.
These beliefs pushed technologies forward. Its stack, formerly developed by Yahoo! and now owned by the Apache Software Foundation, was recognized as “The” Big Data…Continue
Added by Valeria on December 10, 2019 at 7:21am — No Comments
While training the model, we want to get the best possible result according to the chosen metric. And at the same time we want to keep a similar result on the new data. The cruel truth is that we can’t get 100% accuracy. And even if we did, the result is still not…Continue
Added by Igor Bobriakov on December 6, 2019 at 9:00am — No Comments
By 2027, the big data market is estimated to grow to USD 103 billion. And by 2022, the global big data and analytics market is predicted to grow to USD 274 billion, statistics backed by Statista.
The scarcity of talent in the big data industry is being wooed by hefty pay packages, but only to those with extensive knowledge in big data tools and technologies.…Continue
Added by Yoey Thamas on December 3, 2019 at 1:41am — No Comments
A successful business requires new approaches to data management in this age. Modern advances in data science area provide an efficient solutions for numerous use cases.
Data science embraces a broad spectrum of tasks in the sphere of…Continue
Added by Igor Bobriakov on November 27, 2019 at 6:27am — No Comments
Data Scientists help find insights about the market and help make products better. They are responsible for analyzing and handling a massive amount of structured and unstructured data and require various tools to do so. Some of the tools used by Data Scientists to carry out their data operations are mentioned below.
Designed for statistical operations, SAS is an open source proprietary software that is used to…
Added by Simran Agarwal on November 25, 2019 at 3:30am — No Comments
Hadoop is an open-source framework that stores and process big data in a distributed environment using simple programming models. It is designed to scale up from single servers to thousands of machines, while each offers local computation and storage. Hadoop divides a file into blocks and stores across a cluster of machines. It achieves fault tolerance by replicating the blocks on a cluster.
Hadoop can be used as a flexible and easy way for the distributed processing of large…Continue
Added by Yoey Thamas on November 20, 2019 at 1:00am — No Comments
A few years ago I took a call from an analyst at a hedge fund who was looking for external data that would, in his words, provide “alpha.” I explained that our company was connected to thousands of data sources and hundreds of thousands of public datasets; I told him that we were continuously pulling in open data from 70 countries, standardizing it through an ingestion pipeline trained against the largest catalogue of public data in the world, and serving it up…Continue
Added by Lewis Wynne-Jones on November 11, 2019 at 5:30am — No Comments