summarization | stacked LSTM based Network for Text Summarization Using | Natural Language Processing library

I'm trying to use fuzzy string matching to convert strings to specific ids and perform grouped summarization using dplyr. The basic idea is combining imperfect gene sequences into a single gene name via a dictionary lookup approach and counting how many times the gene is detected. This way, counts for sequences aaaaaa and aaaxaa match to gene1 and get added together.

I can do what I want using for and if statements via a row-by-row comparison of the raw data against the dictionary but I find this will be inefficient when I scale up (raw data files have 15k rows on average, the dictionary has 200 rows). Please see my solution below I'm trying to improve and let me know if you can think of a more efficient and elegant way of doing this.

I maxed out the free tier on Atlas and need to reduce the number of documents in my collection by half or more.

Is there a straight forward way to delete N number of documents. I don't need to query or search for specific documents, i just need to mass delete. I have approximately 100k documents in my collection and would like to get it down to around 10k.

I tried db.Articles.deleteMany({10000})and db.Articles.remove(10000)but i know the syntax is wrong

Below is how my documents are stored:

I'm beginner at nlp and I'm using gensim for the first time. I noticed that some text it returns a blank summary. For example:

I'm working at logging an Azure Storage Account. Have a Diagnostic Setting applied and am using Log Analytics to write KQL queries.

My goal is to determine the number of GetBlob requests (OperationName) for a given fileSize (RequestBodySize).

The challenge is that I need to sum the RequestBodySize for all GetBlob operations on each file. I'm not sure how to nest sum in summarize.

Tried so far:

I am trying to build a transformer model for abstractive text summarization task. My dataset is the CNN DM and I am trying to put the features on pandas DataFrame.

My code:

I have a dataframe with the following columns:

I am using the R programming language. I am trying to learn how to summarize text articles by using the following website: https://www.hvitfeldt.me/blog/tidy-text-summarization-using-textrank/

As per the instructions, I copied the code from the website (I used some random PDF I found online):

my task is to make this effect on Scroll I am getting stuck this work on onClick but I need to set it on scroll if someone scrolls it effects work on top fade need to change onClick to onScroll and if you check the sandbox link you can see left side there are 5 headings when I click on first heading effect work but the issue is its call every data I need to set heading with data mean if I click on the first link only first link data appear not all if I click on the second link then only second link data appear

I have a setup of values stored in relatively bigger type of variables, which I have to store in again relatively smaller variables.

Here is the story of the problem: I have different sensor values in different types such as uint16_t, uint32_t and float. I want to store values separated in an uint8_t buffer array to transmit through an RF transmitter. For float type, I accept a finite significant value which then use integer multiplication to store it in an integer variable. Like this:

For this example, I want 3 digits after the comma,