Radek Fabisiak was with the computers from his early days, remembers an orange screen with Win32, big floppy disks, and the sound of dial-up connecting to the internet.
He has got experience in full-stack development by working for top IT companies like Microsoft.
In the last years, in the core team of the Duomly, where as an addition to IT has got skills related to Online Marketing, SEO, Content Creation or building Online Business, now passing this knowledge to the Duomly’s audience.
He is a fan of skiing, video games, cooking, and martial arts in private life.
Loops play an essential role in software development, and they are used to iterate through the arrays or other elements that are iterable. In Javascript, we have a few different types of loops. It sometimes can be confusing which loop we should use in a particular case and which one will be the best in case of our performance. In this article, I’m going to compare the loops in Javascript, describe their pros and cons, test the speed of each of them.
One of the main characteristics of the early 21st century is an outstanding rise in the amount of available data. This is followed by the significant improvements in computational power, storage capacities, as well as the improvements of the algorithms and software for data processing, interpretations, and predictions.
The skills related to data analytics, data science, machine learning, and artificial intelligence are widely demanded and well appreciated. Acquiring such skills requires a significant effort and months or years of learning.
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Intro to machine learning interview questions Machine learning (ML) is a rising field. It offers many interesting and well-paid jobs and opportunities. To start working in machine learning, you should become familiar with:
mathematical fundamentals — linear algebra, calculus, optimization, probability, and statistics, etc.,
machine learning fundamentals — prepare data, validate and improve results, interpret results, recognize and avoid overfitting, etc.,
Python is a popular, general-purpose, and widely used programming language. It’s used for data science and machine learning, scientific computing in many areas, back-end Web development, mobile and desktop applications, and so on. Many well-known companies use Python: Google, Dropbox, Facebook, Mozilla, IBM, Quora, Amazon, Spotify, NASA, Netflix, Reddit, and many more.
Python is free and open-source, as well as most of the products related to it. Also, it has a large, dedicated, and friendly community of programmers and other users.
Intro to Machine learning libraries for Javascript Usually, people apply machine learning (ML) methods and algorithms using one of two programming languages: Python or R. Books, courses, and tutorials about Machine Learning most often use one of these languages as well (or both).
Python is a general-purpose programming language used not only for Machine Learning but for also for scientific computing, back-end Web development, desktop applications, etc. R is created primarily for statisticians.
Natural language processing (NLP) is one of the most promising fields of artificial intelligence that uses natural languages to enable human interactions with machines. There are two main approaches to NLP: – rule-based methods, – statistical methods, i.e., methods related to machine learning.
There are several exciting Python libraries for NLP, such as Natural Language Toolkit (NLTK), spaCy, TextBlob, etc.
A chatbot is a computer software able to interact with humans using a natural language.
Image recognition is one of the most widespread machine learning classes of problems. It aims at training machines to recognize images similarly as people do.
Image recognition belongs to the group of supervised learning problems, i.e., classification problems, to be more precise.
This article presents a relatively simple approach of training a neural network to recognize digits. This approach uses an ordinary feedforward neural network. The accuracy of the model can be further improved using other techniques.
Artificial intelligence (AI) is everywhere around us: image recognition and contacts suggestions on Facebook or Twitter, self-driving cars, software that beats champions in chess and go, books recommendations on Amazon, Google search, Apple Siri and Microsoft Cortana, and so on. It became a very important aspect of our lives. Its importance raises, and we rely on AI more and more every day hoping that it’s going to improve our well-being.
Intro to what is functional programming Functional programming is an interesting programming concept which gains a lot of attention lately. This article presents some of the most important aspects of functional programming in general and provides several examples in Python.
Functional programming is a kind of the declarative programming paradigm where functions represent relations among objects, like in mathematics. Thus, functions are much more than ordinary routines.
This programming paradigm can be implemented in a variety of languages.
Frameworks are a very powerful tool in the development of modern web and mobile applications. Just think about sites and apps like Facebook, Netflix, and Instagram for example. It’s exactly frameworks that are responsible for their uninterrupted operation by providing and giving their users a complete experience.
We can define a framework, most simply, as a large number of pre-built components which give developers the ability to expand and customize them depending on the application they make.