Artificial Intelligence Blog

From SIRI to self-driving cars and from web searches to email communications these days, many things comprise of artificial intelligence that is one of the emerging technologies progressing rapidly each day. It tries to imitate human reasoning in every AI system. It enables the machines to act like a human brain, learning from everything and acting accordingly on every use. But, as everything in excess is dangerous, the same is the case with artificial intelligence. In this article, we will

Have you ever wondered how things around us are becoming smarter as every day passes? How we can perform certain tasks just by a click of a button? And how gadgets can make human-like decisions changing our lives in so many ways? Well, the answers to all these questions lie in two words that are IoT (Internet of Things) and AI (Artificial Intelligence). Both of these technologies are the most powerful technologies today. When we merge them, we get an

Unsupervised Learning is the method of machine learning where a machine learning model tries to understand hidden patterns from our dataset. The dataset here is not labeled and we need not supervise the model whereas in supervised learning the data is labeled. Our ML model will draw inferences from data and groups similar to data from our dataset. The most common algorithms in Unsupervised learning are Clustering, Anomaly Detection, and Neural Networks. These algorithms are computationally complex, takes more time

Supervised Learning in Machine Learning Supervised Learning is the method of machine learning where a machine learning model learns a function from input-output pairs. These examples are labeled that means in a dataset each input is already tagged to some output. Our ML model will learn these examples in the training phase and predict the output if a new input is given. Consider the below example dataset which says whether to decide to play/not given atmosphere properties. Each row is

So, until now, you must be aware of the term machine learning, its types, applications, and working. We have ample information about machine learning. Let’s move to Deep learning and understand it.  Deep learning is the most popular domain of Artificial Intelligence. What is Deep Learning? When we talk about Deep learning, it automatically strikes our mind. Is deep learning is similar to machine learning? If it’s similar what’s the difference which makes deep learning important. Deep Learning is another

Machine Learning is a subset of Artificial Intelligence which instructs machine about the learning process. Working on machine learning entails mainly two types of techniques: Supervised and unsupervised learning. Introduction to Supervised Machine Learning What is Supervised Machine Learning? Supervised Machine Learning is the technique of Machine Learning, which is defined as a task of learning that permits you to either collect or produce data from preceding machine learning implementation. This algorithm collects input data and sent feedback to output

Exploratory Data Analysis (EDA) is a task of analyzing our dataset using simple tools from statistics, from linear algebra and many other plotting tools to understand what our data is conveying us. The term Exploratory here means we try to explore the given data like a detective that we have never seen before. EDA is a very important step in a Machine Learning/Data Science project and for a given problem we first perform EDA and try to get insights from