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Face Recognition using Siamese Network and Triplet Loss

Oct 11, 2020 by Rutvik

Normally, when we train any Machine Learning algorithm, we require lots of similar type of data for the algorithm to train. But, this approach is not effective for tasks like face recognition. Face Recognition aims not only to detect a human face in a given image, but also to recognize whose face it is in the image. But to train such an algorithm in the traditional approach, we will require tens, if not hundreds of images of each person as a different class and train the algorithm to learn to classify the faces. This is not practical as one might not be able to get so many images of a single person. In this article, we imply One Shot Approach for image recognition. This approach enables us to recognize faces using a single image for each person.

Positional Embeddings

Aug 15, 2020 by Rutvik

The Transformers architecture was proposed as a purely attention based sequence to sequence model. Due to its ability of processing the text parallely and its advantage of solving the long sequence dependency problem of RNNs, this architecture has become very popular among researchers for performance improvements. This article discusses about a special part of the architecture, which is the Positional Embeddings.

Introduction to Tokenizers - 1

Aug 08, 2020 by Rutvik

Natural Language Processing, or NLP, for short can be explained as the automated manipulation, or processing of language. This article will walk you through an important concept in NLP, that is Tokenization and different methods and types of tokenizers used.

Linear Regression - Implementation

Dec 08, 2019 by Rutvik

In this article, I will be providing the implementation of Linear Regression both, self-implemented as well as using a pre-built library. The language of usage will be Python and we will be using Scikit Learn as our library.

Linear Regression

Dec 03, 2019 by Rutvik

Before getting into the algorithm of Linear Regression, let us first understand what exactly the term means. The term Linear Regression is created by mixing of two different words: Linear and Regression. So, intuitively, we can guess that the word Linear suggests that it is somewhat related with Linearity, that is related to straight lines. I shall come to this later in the article. But first, it is imperative to know about Regression.

Introduction to Machine Learning

Nov 29, 2019 by Rutvik

Are Artificial Intelligence and Machine Learning different terms? The answer is, absolutely yes. Both the terms, Artificial Intelligence and Machine Learning are different. How? Let us talk about that. This article will talk about a brief but thorough introduction about Machine Learning. So if you are a beginner or want to revise a bit, this is the right article to start with

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Face Recognition using Siamese Network and Triplet Loss

Positional Embeddings

Introduction to Tokenizers - 1

Linear Regression - Implementation

Linear Regression

Introduction to Machine Learning

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