Version Control Systems are a classification of programming instruments that help a product team manage changes to source code over time. Version Control Systems monitor each alteration to the code in a unique sort of database. If a mix-up is made, engineers can compare earlier versions of the code to fix the slip-up while limiting disruption to all other colleagues working on the same project.
For any project, the source code is the most important asset, as it is an archive of the priceless information and comprehension about the problem domain that the engineers have gathered and refined through cautious…
Industrial revolutions only happen once in a blue moon, and yet, we find ourselves in the process of a profound revolution, the Artificial Intelligence (AI) revolution. Over 200 years ago, we experienced the first Industrial Revolution when the steam engine was invented. A century later, we invented electricity, and a century after that, the internet. Like all of these discoveries, artificial intelligence has revolutionized our economy and has disrupted every industry that you can think of.
But first, what makes AI so revolutionary?
Like the steam engine and electricity, AI has extended society’s upper bound on productivity. Unlike humans, who…
When I started to learn about neural networks, I found that the quality of introductory information for such a complex topic didn’t exist. I frequently read that neural networks are algorithms that mimic the brain or have a brain-like structure, which didn’t really help me at all. Therefore, this article aims to teach the fundamentals of a neural network in a manner that is digestible for anyone, especially those that are new to machine learning.
Before understanding neural networks, we need to understand what artificial intelligence and machine learning are.
Imagine a world where credit cards have no hidden fees, no ridiculous interest rates, and also encourage you to develop healthy spending habits…
This has become a reality with the Apple Card.
The Apple Card is a smart credit card that leverages Apple’s technology and was designed to be used synonymously with Apple Pay and Apple devices. In essence, the Apple Card aspired to be everything that a normal credit card wasn’t:
Some people say that ‘Data Science’, ‘Machine Learning’, and ‘Artificial Intelligence’ are nothing more than buzzwords, but I beg to differ.
The Machine Learning (ML) and Artificial Intelligence (AI) industry is MASSIVE, but more importantly, it is GROWING. What started off as a $12 billion industry in 2017 is projected to grow to $57.6 billion by 2021, according to International Data Corporation. That’s an increase of 480% in four years!
Why is ML and AI growing so fast? Because of its potential.
According to McKinsey, organizations that have successfully put ML and AI into production reaped a profit margin increase…
Some say that it’s a buzzword that doesn’t really mean much. Others say that it’s the cause of the end of humanity.
The truth is that artificial intelligence (AI) is starting a technological revolution, and while AI has yet to take over the world, there’s a more pressing concern that we’ve already encountered: AI bias.
AI bias is the underlying prejudice in data that’s used to create AI algorithms, which can ultimately result in discrimination and other social consequences.
Let me give a simple example to clarify the definition: Imagine that I wanted to create an algorithm that…
Do you have a project idea but you don’t know where to start? Or maybe you have a dataset and want to build a machine learning model, but you’re not sure how to approach it?
In this article, I’m going to talk about a conceptual framework that you can use to approach any machine learning project. This framework is inspired by the theoretical framework and is very similar to all of the variations of the machine learning life cycle that you may see online.
A framework in machine learning is important for a number of reasons:
Most problems in the world we deal with have multiple variables. To analyze these variables before they can be fed to a machine learning framework, we need to analytically explore the data. A fast and easy way to do this is bivariate analysis, wherein we simply compare two variables against each other. This can be in the form of simple two-dimensional plots and t-tests.
However, comparing only two variables at a time does not give deep insights into the nature of variables and how they interact with each other. …
Artificial Intelligence (AI) has been a hot topic in the twenty-first century. It’s become so prevalent that there’s a need for over a million AI engineers worldwide,YouTube created a nine-video series on AI, andElon Musk started a company called Neuralink in response to his concerns around AI. AI has almost doubled in interest over the past five years according to Google Trends, but has been around since the 1950’s — Norbert Wiener theorized that all intelligent behavior was the result of feedback mechanisms and this very idea influenced much of the early development of AI. …
Anyone can build a machine learning (ML) model with a few lines of code, but building a good machine learning model is a whole other story.
What do I mean by a GOOD machine learning model?
It depends, but generally, you’ll evaluate your machine learning model based on some predetermined metrics that you decide to use. When it comes to building classification models, you’ll most likely use a confusion matrix and related metrics to evaluate your model. Confusion matrices are not just useful in model evaluation but also model monitoring and model management!
Don’t worry, we’re not talking about linear…