Introduction If you’re working with computer vision, you know that tracking objects in a video stream can be a challenging task. Kalman Filters can be an effective solution to this problem, and when combined with OpenCV and Python, they become even more powerful. In this blog post, we will walk through a Kalman Filter OpenCV […]
Data Science, Machine Learning, Tutorials
Introduction Logistic Regression is a statistical method used for binary classification problems, where the goal is to predict the probability of an event occurring or not. It is a popular algorithm in machine learning, particularly in the field of supervised learning. In this blog post, we will explore the fundamentals of logistic regression and how […]
Data Science, Machine Learning, Tutorials
Introduction K Nearest Neighbors (KNN) is a popular supervised machine learning algorithm that has been widely used in a variety of fields, including marketing, healthcare, and image recognition. It is a simple yet powerful algorithm that belongs to the category of instance-based learning or lazy learning. The KNN algorithm can be applied both for classification […]
Introduction In this blog post we’re going to take a deep dive into support vector classification (SVC) in Python. We will start by looking at the basics of SVC and how it works, before moving on to discuss some of its most important features and parameters. Finally, I’ll show you how easy it is to […]
Data Science, Machine Learning, Tutorials
Introduction In this blog post we’ll be discussing nonlinear regression. In particular, we’ll analyze “polynomial regression”, which is one of the main processes to quickly create a non-linear regression model by expanding the existing data set. Nonlinear regression allows us to […]
Data Science, Machine Learning, Python Basics
Introduction In this blog post, we’ll be exploring Linear Regression in Machine Learning with Python. There are many potential applications for linear regression, especially for your business, including: Sales forecasting: Linear regression can be used to predict future sales based on historical data, such as product pricing, marketing expenses, and consumer demographics. Inventory management: Linear […]
Data Science, Machine Learning
Regression analysis is a commonly used statistical technique for predicting the relationship between a dependent variable and one or more independent variables. In the field of machine learning, regression algorithms are used to make predictions about continuous variables, such as housing prices, student scores, or medical outcomes. Python, being one of the most widely used […]
Analyzing Taylor Swift’s Songs¶ To celebrate Taylor’s new album which has 10 of the top 10 Billboard charts (first time to ever happen), let’s explore Taylor’s discography with the Spotify API. Get credentials from Spotify API¶ Go to your Spotify Dashboard at https://developer.spotify.com/dashboard/ and create a new application, then grab the […]
Data Science, Machine Learning
Deep Learning without labels – Self-Supervised Learning¶ In this blog post we’ll discuss Self-Supervised Learning! Classical supervised learning suffers from four main problems: Fully labelled datasets are expensive or not available at all. There is a large amount of unlabeled datasets which cannot be leveraged by Supervised Learning. Difficuly […]
Analyzing Stock Market Activity of US Senators with Python¶ In 2012, a law called ” Stop Trading on Congressional Knowledge (STOCK) Act of 2012″ was passed, which prohibits the use of non-public information for private profit, including insider trading by members of Congress and other government employees. This law however did not completely […]
