I hate shopping in brick and mortar stores. However, my interest in virtual shopping is not only limited to the buyer experience. With the MobiDev DataScience department, I’ve gained experience in working on AI technologies for virtual fitting. The goal of this article is to describe how these systems work from the inside.
A few years ago, the “try before you buy” strategy was an efficient customer engagement method in outfit stores. Now, this strategy exists in the form of virtual fitting rooms. Fortune Business Insights predicted that the virtual fitting room market size is expected to reach 10.00 …
I know for sure that human behavior could be predicted with data science and machine learning. People lie — data does not. Taking a look at human behavior from a sales data analysis perspective, we can get more valuable insights than from social surveys.
In this article, I want to show how machine learning approaches can help with customer demand forecasting. Since I have experience in building forecasting models for retail field products, I’ll use a retail business as an example.
Moreover, considering uncertainties related to the COVID-19 pandemic, I’ll also describe how to enhance forecasting accuracy.
And don’t worry…
“Is it possible for a technology solution to replace fitness coaches? Well, someone still has to motivate you saying “Come On, even my grandma can do better!” But from a technology point of view, this high-level requirement led us to 3D human pose estimation technology.
In this article, I will describe our own experience of how 3D human pose estimation can be developed and implemented for the AI fitness coach solution.
Human pose estimation is a computer vision-based technology that detects and analyzes human posture. The main component of human pose estimation is the modeling of the human body. …
There’s an old saying that an application is never officially “finished” in the strictest sense — it simply reaches a point where it must be released.
But testing an “old school” monolithic application is one thing. Testing microservices is something else entirely. But what are microservices, and what difference do they make in the grand scheme of things? The answers to these questions are thankfully straightforward — you just need to keep a few key things in mind.
Although microservices are nothing new in web application development, with the big player’s Google and Amazon have been using them for over…
“Why is business analysis so important?” — In fact, some software projects may go without business analysis, but they may take an unpredictably long amount of time.
In this article, I describe the role of a business analyst at each software project stage and share thoughts on how to become a successful business analyst.
Carnegie Mellon University (CMU), which is considered to be the best in preparation of IT specialists, gathered the following statistics about the influence of business analysts on projects:
Artificial Intelligence (AI) is currently being used in marketing and sales for all sorts of processes from personalized shopping to warehouse logistics. Let’s explore how companies can leverage innovations and what algorithms work under the hood.
AI and machine learning enable companies to know their potential customers better, as well as their competitors and other insights about their industry.
With the help of NLP (Natural Language Processing) businesses can analyze customer reviews and comments, social media content, and engagement and turn these raw details into valuable and insightful data. …
Machine learning is a field of research aimed at teaching machines to perform cognitive activity, similar to the human mind. While they are typically much more limited in cognitive ability than the average human, they are able to process vast amounts of information quickly and derive useful business insights.
“The goal of machine learning algorithms is to gain valuable business insights. Here the point is not to get more data, the point is to get the “right” data.”
Liudmyla Taranenko, Data Science Engineer, MobiDev
There won’t be any business insights if the data quality is poor.
When preparing data, I often go through many different approaches to reach a level of quality of data that can provide accurate results. In this article, I describe how unsupervised ML can help in data preparation for machine learning projects and how it helps to get more accurate business insights.
For accurate predictions, the data must not only be properly labeled, de-deputed, broad, consistent, etc. The point is that the machine learning model should process the “right” data. …
Internet of Things (IoT) analytics enables organizations to leverage the massive amounts of data generated by IoT devices, using analytics stacks. IoT analytics is often considered a subset of big data, involved with combining heterogeneous streams and transforming them into consistent and accurate insights.
Insights generated by IoT streams can help organizations improve many aspects of their operations. However, it is often complex to integrate the many types of IoT devices with existing ecosystems and analytics tools. This is why, insofar, organizations deployed Industrial IoT (IIoT), a technology built for collecting and analyzing data from sensors.
When sensors are placed…
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