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Naïve Bayes Algorithm: Everything You Need to Know
Naïve Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks. In this article, we will understand the Naïve Bayes algorithm and all essential concepts so that there is no room for doubts in understanding.
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DBSCAN Clustering Algorithm in Machine Learning
An introduction to the DBSCAN algorithm and its implementation in Python.
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Decision Tree Algorithm, Explained
All you need to know about decision trees and how to build and optimize decision tree classifier.
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 Introduction to AutoEncoder and Variational AutoEncoder (VAE)
Autoencoders and their variants are interesting and powerful artificial neural networks used in unsupervised learning scenarios. Learn how autoencoders perform in their different approaches and how to implement with Keras on the instructional data set of the MNIST digits.
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Advanced Statistical Concepts in Data Science
The article contains some of the most commonly used advanced statistical concepts along with their Python implementation.
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The Inferential Statistics Data Scientists Should Know
The foundations of Data Science and machine learning algorithms are in mathematics and statistics. To be the best Data Scientists you can be, your skills in statistical understanding should be well-established. The more you appreciate statistics, the better you will understand how machine learning performs its apparent magic.
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Hugging Face Transformers Package – What Is It and How To Use It
The rapid development of Transformers have brought a new wave of powerful tools to natural language processing. These models are large and very expensive to train, so pre-trained versions are shared and leveraged by researchers and practitioners. Hugging Face offers a wide variety of pre-trained transformers as open-source libraries, and you can incorporate these with only one line of code.
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Attention mechanism in Deep Learning, Explained
Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works and how to implement the approach into your work.
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Optimization Algorithms in Neural Networks
This article presents an overview of some of the most used optimizers while training a neural network.
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Introduction to Convolutional Neural Networks
The article focuses on explaining key components in CNN and its implementation using Keras python library.
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Introduction to AutoEncoder and Variational AutoEncoder (VAE)
Optimization Algorithms in Neural Networks