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
Summary: Looking at the 12 hottest world-changing segments in the VC-funded world shows that AI will play a key role. Here’s a little more detail.
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
Summary: For all the hype around winning game play and self-driving cars, traditional Reinforcement Learning (RL) has yet to deliver as a reliable tool for ML applications. Here we explore the main drawbacks as well as an innovative approach to RL that dramatically reduces the training compute requirement and time to train.
Added by William Vorhies on December 23, 2019 at 7:30am — 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
Thinking of data science as merely a technical profession, like programming, may take you away from your goals. Focusing on the usability of mathematics for data science before jumping into full-fledged math courses will save you a lot of time.
I wrote this blog post because I made a few mistakes while starting…Continue
Added by Arnuld on December 19, 2019 at 4:00am — No Comments
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
Quite often, non-technical executives have difficulties understanding what programming, on a very fundamental level, is all about. Because of that knowledge-gap, they tend to hire and overburden experienced data professionals with tasks which they are hopelessly overqualified for. Such as, for example, doing ad-hoc SQL queries on CRM data: "You're the go-to-guy for all things data, and we need the results for the board meeting tomorrow." That's a quite humbling and frustrating…Continue
Added by Rafael Knuth on December 5, 2019 at 6:30am — No Comments
Summary: A little history lesson about all the different names by which the field of data science has been called, and why, whatever you call it, it’s all the same thing.
Our profession of…Continue
Added by William Vorhies on December 4, 2019 at 3:12pm — 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
Summary: Too many solutions. We are at an inflection point where too many vendors are offering too many solutions for moving our AI/ML models to production. The very real risk is duplication of effort, fragmentation of our data science resources, and incurring unintended new technical debt as we bind ourselves to platforms that have hidden assumptions or limitations in how that approach problems.
Added by William Vorhies on November 25, 2019 at 9:44am — No Comments