Our strategy for building products

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When we started building our product, we focused on the Recommender engine and Segmentation. As a startup, we embraced agility and focus on the market. At the beginning of 2020, we decided that our product must become a reflection of our team. Then we said it must be a “no bullshit” product, agile or, in …

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How to combine Visual Search and IM

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In this text we will try to briefly explain IM applications integration with Visual Search. You can read more about Visual Search implementation in our last blog post. Instant Messaging (IM) and Chatbots Among all other benefits, The Internet has transformed and simplified how people communicate with each other. In addition to email, IM has …

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Time to Reflect: Our Culture From a Maternity Leave Perspective

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Bonuses and monetary incentives are touted as a cure-all solution for instilling a culture in a company. Fortunately, it will take a touch more than financial incentives to get the culture right. Giving monetary incentives can lead to poor results; look no further than what happened to the Brits in colonial India. The British governor …

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A closer view on Data Science Delivery

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According to Gartner, only 15% to 20% of data science projects get completed. Of those projects that did complete, CEOs say that only about 8% of them generate value. Despite these facts, data science is still considered as an opportunity for business growth. These facts are something that always lingers in the back of everyone’s …

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Be one step ahead: Solver AI Suite short overview

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Intro and motivation In the beginning, it started as the three separate projects. The first one for managing machine learning models known as MoMa, the second one for forecasting using multiple models to give the best results (Fibi), and the third one was a business solution for segmentation and recommender system with personalized view and …

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AI for eCommerce: How to use Visual Search

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Lately we’ve been hearing different kinds of buzzwords all the time – ‘deep learning’, ‘neural networks’, ‘computer vision’, ‘artificial intelligence’… But the explanation of each one of them is actually not so simple. Still, it’s not hard to understand the main concepts of them in order to use it in some real-world applications. One of …

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Things Solver has joined forces with Asseco SEE Group

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This confirms Things Solver’s strategy to continuously enhance its solutions and offer the most advanced products and services to customers Joining forces with the established IT partner ASEE, together we will accelerate the development of existing and new products based on advanced analytics and data processing. We are happy to embark on this new journey, …

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Introduction to recommender systems

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After watching Udemy online course Building Recommender Systems with Machine Learning and AI, I came up with the idea to write a text that can help beginners to understand the basic ideas of the recommender systems. A recommender system, or a recommendation system is a subclass of information filtering system that seeks to predict the …

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Friday talks: EDA done right

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Main challenges  Although EDA is often observed as an initial step which should be straightforward, there are some challenges that could slow down and make this process poor and painful. Some of the challenges I have encountered so far are listed below.  Poorly defined business problem (and not having the understanding of it). Not having …

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HOW TO START WITH DATA SCIENCE?

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After participating in a meetup at the end of March, subjected “Data Science – what is it?”, a lot of people contacted me to send them some introductory materials to help them get started with learning. It took me a long time to sit down and start compiling a list, because there are many sources, …

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FRIDAY TALKS: WOMEN IN DATA SCIENCE

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Hello, fellas. Cool down, I’m not going to talk about extreme feminism and gender (in)equality. 🙂 This post is going to be about extraordinary women I had a chance to meet at the Women in Data Science conference, held in Subotica, this April. I truly believe that these girls deserve to be heard of, as …

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Friday talks: A Data Science Project

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This post is not going to be about another Data Science course you should enroll in. It’s not going to be about various skills you should build in order to develop a Data Science project, either. Considering the title of this post – A Data Science Project – I tried to create a pun. Your …

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Anomaly detection

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The problem of anomaly detection is a very challenging problem often faced in data analysis. Whether it is about clustering, classification or some other machine learning problem, it is of great importance to identify anomalies and handle them in some way, in order to achieve optimal model performances. Furthermore, anomalies could often influence the analysis …

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Handling missing data

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Hi, everyone. Although I planned for my next post to be about anomaly detection and their treatment,  I faced some other type of problem that quickly escalated into huge issue affecting the modelling and results accuracy, and couldn’t resist to share my experience as soon as possible. In this post, I will be talking about …

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Forecasting with VAR and Prophet

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In my previous post, I tried to present the ARIMA model for forecasting. It was based on the use of autoregression and moving average concepts, combining the regression of variable based on its lagged values and calculation of error based on the linear combination of error terms occurred in the past, respectively. In this post, …

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Forecasting with ARIMA

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One of the most challenging machine learning problems is predicting some output based on the history of its previous values. The complexity of the problem multiplies as new features and constraints are added to analysis. Thus, in time series analysis it is not always enough to use previous values only, there often are many features …

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