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deep learning

Batch normalization

Batch Normalisation — Speed up Neural Network Training

What is Normalisation? Normalisation is a technique to change the values of numeric columns in the dataset to a common scale, without distorting differences in the ranges of values. This technique is generally applied as part of data preparation for machine learning and is necessary if various input features are in a different range of […]

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autoencoder

Introduction to Autoencoders? What are Autoencoders Applications and Types?

What are autoencoders Architecture of autoencoders Types of autoencoders Applications of autoencoders Implementation What are Autoencoders Autoencoder is a type of neural network where the output layer has the same dimensionality as the input layer. In simpler words, the number of output units in the output layer is equal to the number of input units

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Transfer learning

Introduction to Transfer Learning | What is Transfer Learning in Deep Learning?

What is Transfer Learning (TL)? How Transfer learning works When to use Transfer Learning (TL)? Transfer learning in NLP(Natural Language Processing) Use TL to detect COVID-19 What is Transfer Learning? Transfer learning is a research problem in Deep learning (DL) that focuses on storing knowledge gained while training one model and applying it to another

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neural network

3 Things to know before Deep diving into Neural Networks

With Artificial Intelligence and its technology taking over the world, the demand and the interest around the study peaks an upward graph. The hype surrounding AI boils down to its most basic cornerstone – neural networks. If you are a tech fanatic, and if you have managed to tweak your attention towards deep-diving into neural

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prerequisites deep learning

Things to know before You Deep Dive into Deep Learning

You and I live in a world where, for better and for worse, we are constantly surrounded by algorithms. From song recommendations to driverless cars, and from financial fraud detection to medical image processing. Every sector has benefitted from the rapid incorporation of deep learning algorithms. The advancement of deep learning techniques has opened a

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Datasets for Computer Vision

Datasets for Computer Vision using Deep Learning

Deep learning stems from neural network-based artificial intelligence. Neural networks transformed the entire learning process of algorithms due to its efficient feature extraction capabilities. The deep learning approach has gained tremendous momentum in the past decade for the following reasons: Large and efficient datasets Huge rise in computational power capabilities The best time to learn

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Artificial Intelligence versus Machine Learning versus Deep Learning

The heading of this article comprises of the most searched keywords on Google today in the field of computer science. Every scholar, researcher has very high hopes and plans to solve the problems on our planet using these technologies. What makes artificial intelligence, intelligent? The answer to that question lies in the application under consideration.

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