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#001 OpenCV projects – Face Tracking with OpenCV using Haar cascade detectors

11.09.2020

Highlights: This will be our introductory post where we will explain the difference between object detection and object tracking. We will learn the easiest way to track objects and in this case, it will be a face detection. We will admit that we are cheating a bit because we are not using tracking algorithms. Due to the simplicity of this post as a simple introduction, we are going to use Viola-Jones face detection algorithm. In…
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#004 OpenCV projects – How to extract features from the image in Python?

10.09.2020

Highlights: In this post, we are going to show how to detect distinct features in an image. We will describe the important properties of these features (keypoints) and we will learn how we can use them to better understand the structure and the content of an image. Furthermore, we will talk about the most common algorithms that can be used for feature detection. So, let’s begin. Tutorial overview: What are keypoints? Detecting corners with Harris…
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#003 PyTorch – How to implement Linear Regression in PyTorch

23.08.2020

Highlight: In this post we are going to explain what a Liner regression is. After covering the basic theory behind Linear regression, we are going to code a simple linear regression model in Python using PyTorch library. So, let’s begin. Tutorial overview: What is a linear model? Building a linear model Linear regression Loss function Calculating the Mean Squared Error (MSE) Cost graph Gradient descent Linear regression in PyTorch Intuitive implementation of Linear regression in…
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#005 PyTorch – Logistic Regression in PyTorch

23.08.2020

Highlights: In this post, we are going to talk about logistic regression. We will first cover the basic theory behind logistic regression and then we will see how we can apply this knowledge in PyTorch.   Tutorial Overview: What is a binary prediction? Logistic regression – introduction A cost function optimization Cross–entropy loss function Calculating Logistic regression derivatives Logistic regression in Python with PyTorch Simple example Logistic Regression experiment 1. What is a binary prediction?…
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#012 Principal Component Analysis (PCA)

10.07.2020

Highlight: In this post, we will discuss the Principle Component Analysis (PCA). PCA is the bedrock dimensionality reduction technique for probability and statistics. It is commonly used in Data Science and Machine Learning Applications to deal with high-dimensional data that have some statistical distribution. Our goal is to use PCA and uncover the low-dimensional patterns to build models. Before we learn about PCA, we need to understand several steps. First, we will learn about the…
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The hundred-page Computer Vision book
What are morphological transformations?
Learn how to align Faces in OpenCV in Python

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