Deep Learning

Deploying a Deep Learning Skin Classification App to Google Cloud

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A Step-by-Step Guide In this guide, we’ll walk you through the process of deploying a deep learning skin classification application to Google Cloud Run. Cloud Run is a fully managed platform that automatically scales your containerized applications, making it an ideal choice for deploying machine learning models. Whether you’re a data scientist or a developer, …

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Skin Cancer Classification Web App, Docker, and Azure Cloud

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In this comprehensive blog, we will walk you through the process of creating and deploying a Deep Learning-based image classification project. We will focus on classifying skin cancer images into benign and malignant categories using modern technologies. The journey will cover training a deep learning model, building a Flask web application, managing version control with …

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Traffic Sign Classification with 47 Classes: A Deep Learning Journey

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[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 …

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Titanic dataset classification Python

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To classify the Titanic dataset using Python, you will need to follow these steps: Here is an example of how you could classify the Titanic dataset using Python: This code first imports the necessary libraries, then loads the data using Pandas, explores the data, preprocesses the data by dropping missing values and encoding categorical variables, …

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Dimensionality Reduction

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Dimensionality reduction is a method used to reduce the number of features or dimensions in a dataset. This is often done to reduce the complexity of the data, make it easier to visualize, or to improve the performance of machine learning algorithms. There are many different techniques for dimensionality reduction, including: Dimensionality reduction can be …

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Difference between AI, Data Science, ML, and DL

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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 …

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Morphological operations

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Morphological operations are a set of image processing operations that are performed on binary images. These operations are based on the shape of the objects in the image, and are used to extract structural information from the image. Some common morphological operations include dilation, erosion, opening, closing, and skeletonization. These operations can be used to …

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Generative Adversarial Network (GAN)

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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 …

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