In simple terms, a decision tree is a data analysis tool that can be used to make decisions. It’s an efficient way to analyze large sets of data and identify patterns. More importantly, decision trees are commonly used in machine learning. This is a field of AI that uses computers to learn from data and … Read more
Artificial intelligence and machine learning have been around for a while now, but what exactly is it? Simply put, AI and ML are technologies that allow machines to learn from data. In other words, they can “figure things out” on their own by analyzing large amounts of data. This technology is being used in a … Read more
Like most people, you probably think of machine learning as a way to make computers smarter. You may have heard of it in the context of Google Photos, which identifies objects in photos and tags them accordingly. But you may not know that machine learning has much more to offer than just powering Google Photos … Read more
In a nutshell, epoch is a term used in machine learning that stands for an “epoch” of data. Epochs are used to divide data into manageable chunks, making it easier for algorithms to learn from (and, ultimately, predict future outcomes). Obviously, this makes epochs incredibly important when it comes to machine learning; without them, the … Read more
In this article, we will be discussing the concept of classification in machine learning. We will start off by giving an overview of the different types of classification that are available, and then move on to describe how they work. We will also provide a few examples to illustrate the concepts more clearly. What is … Read more
Let’s us try to implement logistic regression from scratch in python. Recommended to be read after the Neural Networks release. To test and run the code used check out: https://www.kaggle.com/code/tanavbajaj/logistic-regression-math-behind-without-sklearn Importing necessary libraries import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) import matplotlib as … Read more
Under supervised learning, there is a type called classification. These algorithms are used to recognise the category a new observation belongs to based on the training dataset. In supervised learning, there are independent variables and a dependent variable Here, the dependent variable is the category, and each category’s features are independent variables. These categories are … Read more
Under supervised learning, there is a type called classification. These algorithms recognize the category a new observation belongs to based on the training dataset. In supervised learning, there are independent variables and a dependent variable Here, the dependent variable is the category, and each category’s features are independent variables. These categories are distinct and pre-defined … Read more
