Gaussian NAIVE BAYES, continuous features
There are different variants of Naive bayes , bernoulli, and Gaussian. This article assumes you are familiar with the the basic idea behind Naive bayes and also how it works …
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THE WORD2VEC MODEL (CBOW /SKIP-GRAM)
Understanding Word embeddings ,Semantics , and Word2vec model methods like skipgram and CBOW. WHY embeddings? remember machines can only operate on numbers . approaches like Bag of words ,tfidf provide …
Understanding Transformers (NLP )
In this article we will try to understand the complex “transformers” structure , there are a lot of components involved within the structure and i hope you are familiar with …
THE PROBLEM IN SIMPLE RNN ENCODER DECODER MODELS ,BIDIRECTIONAL ENCODERS,LSTMS(BLOG)
IF YOU KNOW THE BASIC ARCHITECTURE OF AN ENCODER DECODER MODEL , YOU WILL RECOGNIZE TE PICTURE BELOW : WHERE ” C” IS THE CONTEXT VECTOR . IN SHORT THIS …
THE PROBLEM IN SIMPLE RNN ENCODER DECODER MODELS ,BIDIRECTIONAL ENCODERS,LSTMS(BLOG) Read More »
K-means failure cases for interviews
Here we discuss the failure cases of the K-means algorithm . As we know , k-means is one of the most commonly asked algorithm in interviews its advisable to know …
REINFORCEMENT LEARNING
THE WHAT AND HOW OF REINFORCEMENT LEARNING APART FROM SUPERVISED AND UNSUPERVISED MACHINE LEARNING , THERE IS A THIRD KIND OF MACHINE LEARNING APPROACH , WIDELY KNOWN AS REINFORCEMENT LEARNING …