ResNet And DenseNet Implementation In Depth
In recent years, convolutional neural networks (CNNs) have revolutionized the field of computer vision, enabling machines to recognize patterns, classify ...
Tag: Supervised Learning
Convolutional Neural Networks (CNNs): Concept And Application
In the previous tutorial on Introduction to Artificial Neural Networks (ANNs), we explored the fundamentals of deep learning and witnessed ...
[In Depth] Nearest Neighbors: Concept And Application
In this tutorial, we will learn our next machine-learning model called nearest neighbors (NN), known as k-nearest Neighbors (k-NN). It ...
A Beginner’s Guide to Data Preprocessing In ML
Welcome to a beginner's guide to data preprocessing in machine learning. In the previous few tutorials, we saw some basic ...
[In Depth] Stochastic Gradient Descent: Concept And Application
If you have been following my previous tutorials, you must be familiar with other optimization techniques to solve ML problems. ...
[In Depth] Logistic Regression: Concept And Application
In our last tutorial, we discussed naive Bayes, a nifty tool for categorizing things. Now, let's delve into logistic regression, ...
[In Depth] Linear Regression: Concept And Application
Imagine you are a real estate agent trying to estimate the price of a house based on its size. You've ...
Probability Calibration in Machine Learning
Probability calibration is the key to unlocking the true potential of machine learning models, ensuring that the predicted probabilities align ...
[In depth] Naive Bayes: Concept And Application
In this tutorial, we will learn our next machine-learning model called Naive Bayes. Naive Bayes is widely recognized as a ...
[In Depth] Random Forests & Ensemble Learning: Concept And Application
In this tutorial, we are going to learn an advanced concept related to decision trees called random forests. The idea ...