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Analyzing and Comparing Deep Learning Models

Analytics Vidhya

Deep Learning Overview Deep Learning is a subset of Machine Learning. Deep Learning is established on Artificial Neural Networks to mimic the human brain. In deep learning, we add several hidden layers to gather the most minute details to learn the data for […].

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Visualizing Model Insights: A Guide to Grad-CAM in Deep Learning

Analytics Vidhya

Introduction Gradient-weighted Class Activation Mapping is a technique used in deep learning to visualize and understand the decisions made by a CNN. This groundbreaking technique unveils the hidden decisions made by CNNs, transforming them from opaque models into transparent storytellers.

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Image Classification Using Resnet-50 Deep Learning Model

Analytics Vidhya

Introduction In this article, we will train a classification model which uses the feature extraction + classification principle, i.e., firstly, we extract relevant features from an image and then use these feature vectors in machine learning classifiers to perform the final classification. We will […].

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Deploying Deep Learning Model Using Tkinter and Pyinstaller

Analytics Vidhya

Introduction Machine Learning and Deep Learning models are often created and run either in the Jupyter notebook or in IDE. Very few of them get deployed, and the deployment of these models usually tends to be website based. Rarely do developers convert them into standalone apps due to a lack of not knowing how?

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How to Make an Image Classification Model Using Deep Learning?

Analytics Vidhya

Introduction In the 21st century, the world is rapidly moving towards Artificial Intelligence and Machine Learning. Various robust AI Models have been made that perform far better than the human brain, like deepfake generation, image classification, text classification, etc. appeared first on Analytics Vidhya.

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Amplifying Deep Learning: A Dive into Data Augmentation Strategies

Analytics Vidhya

Introduction In the world of deep learning, where data is often less, the role of data augmentation has become very important. We use methods like turning images or flipping them to make our model learn better. But our datasets are becoming more complicated. That’s where data augmentation steps in.

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Deep learning model to predict mRNA Degradation

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Designing a deep learning model that will predict degradation rates at each base of an RNA molecule using the Eterna dataset comprising over 3000 RNA molecules. The post Deep learning model to predict mRNA Degradation appeared first on Analytics Vidhya.