Say Hello to Artificial Intelligence
Say Hello to Artificial Intelligence
[Introduction] Traffic signs are everywhere on our roads, ensuring safety and efficient traffic flow. But what if we could teach a computer to understand and interpret these signs, just like humans do? That’s exactly what we’re going to explore in this video. [Project Overview] In this project, we trained a deep learning model to classify …
Traffic Sign Classification with 47 Classes: A Deep Learning Journey Read More »
Some common deep learning algorithms include convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks. These algorithms are all types of neural networks that are designed to work with large amounts of data and to automatically learn from that data. CNNs are often used for image recognition tasks, RNNs are …
There are many different types of machine learning algorithms, and the best algorithm for a particular problem will depend on the specific characteristics of the data and the desired outcome. Some common types of machine learning algorithms include: These are just a few examples of common machine learning algorithms. There are many other algorithms that …
Difference between Artificial intelligence, Data Science, Machine Learning, and Deep Learning Artificial intelligence: Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and act like humans. These machines are trained to perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language …
Python list comprehension is a syntax for creating a new list from an existing list, typically using a for loop to iterate over the original list and evaluating an expression for each element to create a new element for the new list. List comprehension is a convenient and concise way to create lists, and it …
A Generative Adversarial Network (GAN) is a type of machine learning model that is composed of two parts: a generator and a discriminator. The generator model generates fake data, such as fake images, while the discriminator model attempts to classify the fake data as real or fake. The generator and discriminator models are trained together …
Machine learning is a method of teaching computers to learn from data, without being explicitly programmed. It involves using algorithms to analyze and understand complex data, and to make predictions or decisions based on that data. There are many different types of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, …
Support Vector Machines (SVM) is a type of supervised machine learning algorithm that is commonly used for classification and regression tasks. It works by finding the best boundary or decision surface that separates the different classes in the data. This boundary is called the hyperplane and the points that are closest to it are called …
A convolutional neural network (CNN) is a type of deep learning model that is commonly used for image classification and other tasks that involve analyzing visual data. CNNs are composed of multiple layers, including convolutional layers, pooling layers, and fully connected layers. The convolutional layers of a CNN are responsible for extracting features from the …
As I mentioned in my previous blog, face mask detection uses deep learning techniques. In this blog, you will learn how to accurately detect the face mask and classify it into two categories (face mask and no face mask). For this purpose, first, we trained the deep learning CNN model (MOBILE NET) using the facemask …