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Customer feedback: The ultimate guide

Reading time19 min
Views2.4K

Introduction

It was 1989 when 2 editors of Inc. magazine, George Gendron and Bo Burlingham made the nervous drive to Palo Alto, California. Not long beforehand they’d decided on who to name as Inc.’s Entrepreneur of the Decade, and finally, they would get a chance to interview him.

As they entered the offices of NeXT, their interviewee approached them. In his trademark jeans and turtleneck sweater, Steve Jobs led them up the stairs to his office and the interview commenced.

Securing an interview with Steve Jobs was rare, even in 1989. And, wanting to make the most of their time, the editors got straight to the point with their very first question:

“Where do great products come from?”

After a slight pause, and a shuffle in his chair, Jobs replied:

“I think really great products come from melding two points of view; the technology point of view and the customer point of view. You need both. You can't just ask customers what they want and then try to give that to them. By the time you get it built, they'll want something new.”

Silence overshadowed the room. Three decades later, and this powerful answer Jobs gave is something that still isn’t often internalized in companies. 

Collecting user feedback is incredibly important. As you’ll see examples of later in this article, launching surveys, asking onboarding questions, and conducting customer interviews are all vital tools for improving your product. 

But the true lesson that Steve Jobs gave all this time ago was that user feedback isn’t as simple as asking what users want, or what they think about your product, and making those changes. You have to dive much deeper.

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Total votes 4: ↑4 and ↓0+4
Comments2

Benefits of Hybrid Data Lake: How to combine Data Warehouse with Data Lake

Reading time4 min
Views2.2K

Hey, hey! I am Ilya Kalchenko, a Data Engineer at NIX, a fan of big and small data processing, and Python. In this article, I want to discuss the benefits of hybrid data lakes for efficient and secure data organization.

 To begin with, I invite you to figure out the concepts of Data Warehouses and Data Lake. Let’s delve into the use cases and delimit areas of responsibility.

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$mol_func_sandbox: hack me if you might!.

Reading time6 min
Views1.8K

Hello, I'm Jin, and I… want to play a game with you. Its rules are very simple, but breaking them… will lead you to victory. Feel like a hacker getting out of the JavaScript sandbox in order to read cookies, mine bitcoins, make a deface, or something else interesting.



https://sandbox.js.hyoo.ru/


And then I'll tell you how the sandbox works and give you some ideas for hacking.

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Total votes 3: ↑3 and ↓0+3
Comments5

Q1 2021 DDoS attacks and BGP incidents

Reading time6 min
Views1.6K

The year 2021 started on such a high note for Qrator Labs: on January 19, our company celebrated its 10th anniversary. Shortly after, in February, our network mitigated quite an impressive 750 Gbps DDoS attack based on old and well known DNS amplification. Furthermore, there is a constant flow of BGP incidents; some are becoming global routing anomalies. We started reporting in our newly made Twitter account for Qrator.Radar.

Nevertheless, with the first quarter of the year being over, we can take a closer look at DDoS attacks statistics and BGP incidents for January - March 2021.

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Total votes 15: ↑15 and ↓0+15
Comments0

Only 39% of the functions in node_modules are unique in the default Angular project

Reading time21 min
Views2.7K

Only 39% of the functions in node_modules are unique in the default Angular project created by ng new my-app.


I think the developers of open source solve problems in the same ways, because they study the same algorithms. Well, why be honest, they copy the popular solutions from StackOverflow also.


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Flitter Your Business With AI Integrated Flutter App Development

Reading time5 min
Views2.9K

As we all are aware of the fact that the digital market is heavily leaning towards a reliable UX-driven process, app development has become quite complex, especially for targeting the industry for mobile platforms.

For every organization, creating a product that is beneficial for their customer needs always comes up with a plethora of challenges. 

From the technical point of time, there are various challenges that every business faces, including selecting the right platform for the app, the right technology stack or framework, and creating an app that fulfills the needs and expectations of customers.  

Similarly, there are more challenges that every business faces and needs to cope with while creating its dream product. 

So, what to do??

Well, what if I say that the answer to all your queries and questions is Flutter app development with Artificial Intelligence (AI)  integration……

Surprised? Wondering how? 

Well, AI in Flutter app development is one of the best advancements in the software market. The concept of AI was first introduced during the 20th century with loads of innovations and advancements that we are still integrating into our mobile app development. 

But, what are Artificial Intelligence and Flutter app development? 

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Go Rant: Highly Opionated View About Reaches and Gotchas of Goland

Reading time4 min
Views1.5K

In this series, I would like to discuss some reaches of Go programming language. There is no shortage of Go-Language-Of-Cloud style articles in which you can explore the great benefits that Go indeed provides. However, there are lees to every wine, and Go does not go without blemish. In this highly opinionated series, we cover some controversies and, dare I say, pitfalls of the original Go design.


We start tough and begin with the essence of Go — it's inbuild data types. In this article, we put slice to the test. Let's move a step further from the Go Tour and use slice more extensively. For example, there is no separate data type as stack in Go, because slice type is intended to cover all its usage scenarios.


Let's briefly recap the usage of the stack. We can create a stack in two seconds using a couple of paper stickers. You write "buy milk" on the first sticker and put at the desk, and then "make the dishes" on the second and pile it on the first sticker. Now, you have a stack: the dishes sticker came last but will be served first, as it is on the top of the stack. Thus, there is an alternative name for stack — LIFO, Last-In-First-Out. To compare, there is the "opposite" data structure queue or FILO — first in, first out. In programming, stacks are everywhere, either in the explicit form or in the implicit as stack trace of the execution of a recursive function.


Ok, let's put slice into use and implement stack.

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Context category

Reading time12 min
Views1.4K

The mathematical model of signed sequences with repetitions (texts) is a multiset. The multiset was defined by D. Knuth in 1969 and later studied in detail by A. B. Petrovsky [1]. The universal property of a multiset is the existence of identical elements. The limiting case of a multiset with unit multiplicities of elements is a set. A set with unit multiplicities corresponding to a multiset is called its generating set or domain. A set with zero multiplicity is an empty set.

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Total votes 1: ↑1 and ↓0+1
Comments0

Roslyn API: Why PVS-Studio Was Analyzing the Project So Long

Reading time3 min
Views642

How many of you have used third-party libraries when writing code? It's a catchy question. Without third-party libraries the development of some products would be delayed for a very, very long time. One would have to reinvent the wheel to solve each problem. When you use third-party libraries you still stumble upon some pitfalls in addition to obvious advantages. Recently PVS-Studio for C# has also faced one of the deficiencies. The analyzer could not finish analyzing a large project for a long time. It was due to the use of the SymbolFinder.FindReferencesAsync method from the Roslyn API in the V3083 diagnostic.

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Total votes 2: ↑1 and ↓10
Comments0

You are standing at a red light at an empty intersection. How to make traffic lights smarter?

Reading time14 min
Views2.1K

Types of smart traffic lights: adaptive and neural networks

Adaptive works at relatively simple intersections, where the rules and possibilities for switching phases are quite obvious. Adaptive management is only applicable where there is no constant loading in all directions, otherwise it simply has nothing to adapt to – there are no free time windows. The first adaptive control intersections appeared in the United States in the early 70s of the last century. Unfortunately, they have reached Russia only now, their number according to some estimates does not exceed 3,000 in the country.

Neural networks – a higher level of traffic regulation. They take into account a lot of factors at once, which are not even always obvious. Their result is based on self-learning: the computer receives live data on the bandwidth and selects the maximum value by all possible algorithms, so that in total, as many vehicles as possible pass from all sides in a comfortable mode per unit of time. How this is done, usually programmers answer – we do not know, the neural network is a black box, but we will reveal the basic principles to you…

Adaptive traffic lights use, at least, leading companies in Russia, rather outdated technology for counting vehicles at intersections: physical sensors or video background detector. A capacitive sensor or an induction loop only sees the vehicle at the installation site-for a few meters, unless of course you spend millions on laying them along the entire length of the roadway. The video background detector shows only the filling of the roadway with vehicles relative to this roadway. The camera should clearly see this area, which is quite difficult at a long distance due to the perspective and is highly susceptible to atmospheric interference: even a light snowstorm will be diagnosed as the presence of traffic – the background video detector does not distinguish the type of detection.

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Total votes 3: ↑3 and ↓0+3
Comments0

Data Science Digest — 21.04.21

Reading time3 min
Views989

Hi All,

I’m pleased to invite you all to enroll in the Lviv Data Science Summer School, to delve into advanced methods and tools of Data Science and Machine Learning, including such domains as CV, NLP, Healthcare, Social Network Analysis, and Urban Data Science. The courses are practice-oriented and are geared towards undergraduates, Ph.D. students, and young professionals (intermediate level). The studies begin July 19–30 and will be hosted online. Make sure to apply — Spots are running fast!

If you’re more used to getting updates every day, follow us on social media:

Telegram
Twitter
LinkedIn
Facebook

Regards,
Dmitry Spodarets.

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Total votes 3: ↑2 and ↓1+1
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Neural network Telegram bot with StyleGAN and GPT-2

Reading time3 min
Views5K

The Beginning


So we have already played with different neural networks. Cursed image generation using GANs, deep texts from GPT-2 — we have seen it all.


This time I wanted to create a neural entity that would act like a beauty blogger. This meant it would have to post pictures like Instagram influencers do and generate the same kind of narcissistic texts. \


Initially I planned to post the neural content on Instagram but using the Facebook Graph API which is needed to go beyond read-only was too painful for me. So I reverted to Telegram which is one of my favorite social products overall.


The name of the entity/channel (Aida Enelpi) is a bad neural-oriented pun mostly generated by the bot itself.


One of the first posts generated by Aida

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Comments1

Data Science Digest — We Are Back

Reading time5 min
Views1.1K

Hi All,

I have some good news for you…

Data Science Digest is back! We’ve been “offline” for a while, but no worries — You’ll receive regular digest updates with top news and resources on AI/ML/DS every Wednesday, starting today.

If you’re more used to getting updates every day, follow us on social media:

Telegram - https://t.me/DataScienceDigest
Twitter - https://twitter.com/Data_Digest
LinkedIn - https://www.linkedin.com/company/data-science-digest/
Facebook - https://www.facebook.com/DataScienceDigest/

And finally, your feedback is very much appreciated. Feel free to share any ideas with me and the team, and we’ll do our best to make Data Science Digest a better place for all.

Regards,
Dmitry Spodarets.

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Qrator Labs' Value Partnership Programs

Reading time3 min
Views945

Why is it valuable to get into the Qrator Labs partnership program?

In Qrator Labs, we firmly believe that working together brings a better result. Which is the reason why, for years, we were trying to find meaningful partnerships with all kinds of companies. They either seek to provide their existing customers with the top-notch DDoS mitigation technology developed at Qrator Labs with many additional ecosystem solutions or want to succeed the other way around. By getting their product available for Qrator Labs' customers by integrating into the Qrator anycast filtering network.

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Total votes 20: ↑20 and ↓0+20
Comments0

Algorithms in Go: Bit Manipulation

Reading time5 min
Views3.2K

This article is a part of Algorithms in Go series where we discuss common algorithmic problems and their solution patterns.


In this edition, we take a closer look at bit manipulations. Bit operations can be extremely powerful and useful in an entire class of algorithmic problems, including problems that at first glance does not have to do anything with bits.


Let's consider the following problem: six friends meet in the bar and decide who pays for the next round. They would like to select a random person among them for that. How can they do a random selection using only a single coin?



The solution to this problem is not particularly obvious (for me:), so let's simplify a problem for a moment to develop our understanding. How would we do the selection if there were only three friends? In other words, how would we "mimic" a three-sided coin with a two-sided coin?

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Total votes 2: ↑2 and ↓0+2
Comments0