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LSTM (Long Short Term Memory) is a variant of Recurrent Neural Network architecture (RNNs). LSTM solves the problem of vanishing and exploding gradients during backpropagations. This is achieved by using a memory cell. In this post, we will discuss the weight and bias dimensions of the LSTM cell. For understanding the LSTM, you can refer here or here.

Architecture of LSTM

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One of the basic and first algorithms that people learn in the machine learning domain is TF-IDF vectorization. TF-IDF stands for Term Frequency and Inverse Document frequency.

Here we will try to see how exactly TF-IDF works and will compare our results to the sklearn library. We will not go much into details about how it is useful as compared to other algorithms.

What is TF-IDF?

TF-IDF is a statistical tool that measures how relevant a word is to a document in a bunch of documents.

It consists of two parts :
1. Term Frequency (TF): how many times a word appears in a…

Last winter (Dec-Jan 20–21), I got an opportunity to undergo an online (due to Covid-19) Winter Training Program at Institute of Drilling Technology (IDT) Completion Fluid (R&D)Technology Group, ONGC, Dehradun from 28 Dec 2020 to 27 January 2020.


You can visit their site to know more-

Institute of Drilling Technology (IDT) provides its techno-economic expertise & solutions to various field problems faced by various services of ONGC with the ultimate objective to promote cost effective E&P activities of the company. …

petroleum refinery


The terms petroleum refining and petrochemical industry are two different terms people often confuse between. When the crude oil is processed to give fuels such as gasoline, diesel, kerosene, jet fuel etc., then we name the process as petroleum refining whereas when products from refining are further treated (in various units such as isomerisation unit, hydrocracking etc.) to obtain more valuable products is known as petrochemistry. For eg. Naphtha(direct product from refining) is commonly used to make ethenes, propenes, butenes, which form plastics(valuable material).


20% of the world’s data is stored in a Structured way in the form of Relational Database.

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Being a Computers student you might have come across one of the most important topics in Database Management Systems that is Database Normalization. Normalization being a hot topic of discussion in Campus Placements Interviews, for PSUs & gate exams, for research as well. In this blog, I will discuss the various Normalization techniques & will show you how can you find the Highest Normal forms for the tables very easily.

Before jumping to the main topic let me introduce you to the evolution…

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Principal component analysis (PCA) is a statistical procedure that is used to reduce the dimensionality. It uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. It is often used as a dimensionality reduction technique.

Steps Involved in the PCA

Step 1: Standardize the dataset.

Step 2: Calculate the covariance matrix for the features in the dataset.

Step 3: Calculate the eigenvalues and eigenvectors for the covariance matrix.

Step 4: Sort eigenvalues and their corresponding eigenvectors.

Step 5: Pick k eigenvalues and form a matrix of eigenvectors.

Step 6…

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