Big data is a term that describes datasets that are too large to be processed with the help of conventional tools and also is sometimes used to call a field of study that concerns those datasets. In this post, we will talk about the benefits of big data and how businesses can use it to succeed.
Today, we will look at a rather old and somewhat quirky. language that most of you probably don’t have on your radars.
While Erlang is not as popular as some modern programming languages, it quietly runs applications like WhatsApp and WeChat that serve massive amounts of users every day.
In this article, I will tell you more about this language, its history, and whether you should think about learning it yourself.
Erlang is a functional, general-purpose language oriented towards building scalable, concurrent systems with high availability guarantees.
It was built at the end of the 1980s at Ericsson for handling telephone switches. At the time, telephone switching systems were one of the most complicated systems out there, like the internet is nowadays. For this reason, the language used to program them needed to support high concurrency and zero downtime. …
Language is a logical structure that, in theory, should be easy for a machine to work with. How difficult is it, really, to train an ML text analysis system? Let’s find out today.
Text analysis is the process of obtaining valuable insights from texts.
ML can work with different types of textual information such as social media posts, messages, and emails. Special software helps to preprocess and analyze this data.
Text analysis and text mining are synonyms. They describe the same process of extracting meaning from data by observing patterns.
However, text analysis and text analytics are a bit different…
The principal goal of machine learning is to create a model that performs well and gives accurate predictions in a particular set of cases. In order to achieve that, we need machine learning optimization.
Machine learning optimization is the process of adjusting the hyperparameters in order to minimize the cost function by using one of the optimization techniques. It is important to minimize the cost function because it describes the discrepancy between the true value of the estimated parameter and what the model has predicted.
In this article, we will discuss the main types of ML optimization techniques.
Before we go any further, we need to understand the difference between parameters and hyperparameters of a model. These two notions are easy to confuse, but we should not. …
If you haven’t yet heard, Rust is one of the most promising and most loved programming languages out there.
First created at Mozilla, it has since been adopted by companies like Dropbox, Microsoft, Facebook, and others. Rust’s main benefit is that it enables C-like performance while still keeping the memory safety that we are used to when developing with languages like JavaScript and Python.
In this article, I will look at nine large companies that use Rust and delve into the reasons for their choice.
In this article, we’ll discuss some strategies for effective ML testing. You will learn how to test and evaluate models, overcome common bottlenecks, and more.
First of all, what are we trying to achieve when performing ML testing, as well as any software testing whatsoever?
One of the most common applications of machine learning is pattern recognition. Computers that use well-trained algorithms recognize animals in photos, anomalies in stock fluctuations, and signs of cancer in mammograms much better than humans do. Let us find out what lies behind this complex process.
Pattern recognition is the process of recognizing regularities in data by a machine that uses machine learning algorithms. In the heart of the process lies the classification of events based on statistical information, historical data, or the machine’s memory.
A pattern is a regularity in the world or in abstract notions. If we talk about books or movies, a description of a genre would be a pattern. If a person keeps watching black comedies, Netflix wouldn’t recommend them heartbreaking melodramas. …
As a subset of artificial intelligence, deep learning lies at the heart of various innovations: self-driving cars, natural language processing, image recognition, and so on. Companies that deliver DL solutions (such as Amazon, Tesla, Salesforce) are at the forefront of stock markets and attract impressive investments. According to Statista, the total funding of artificial intelligence startup companies worldwide in 2014–2019 is equal to more than $26 billion. This high interest can be explained by the amazing benefits of deep learning and its architectures — artificial neural networks.
Fintech is one of the biggest and fastest-growing IT markets today.
It is an emerging industry that uses technology to compete with traditional financial methods in the delivery of financial services. Mobile banking, investing services, and cryptocurrency are all solutions that make financial services more accessible to the general public.
One significant trend that we have witnessed in fintech is the use of functional programming languages. In this blog post, we will delve deeper into the state of fintech right now, and how exactly functional programming can improve modern fintech products. …
One of the main advantages of Elixir is that it is awesome for server-side systems. Forget using a million different technologies for things like data persistence, background jobs, and service crash recovery, OTP can supply you with everything.
So what exactly is this magical thing?
In this article, I will introduce you to OTP, look at basic process loops, the GenServer and Supervisor behaviours, and see how they can be used to implement an elementary process that stores funds.
(This article assumes that you are already familiar with the basics of Elixir. If you’re not, you can check out the Getting Started guide on Elixir’s website or use one of the other resources listed in our Elixir guide.) …
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