Count Vectorization in NLP | Natural Language Processing | Python | NLP | Code Warriors

We are welcoming all of you on this tutorial.

In this video we will discuss about basics of Count Vectorizationin NLP.

The essence of Natural Language Processing lies in making computers understand the natural language. That’s not an easy task though. Computers can understand the structured form of data like spreadsheets and the tables in the database, but human languages, texts, and voices form an unstructured category of data, and it gets difficult for the computer to understand it, and there arises the need for Natural Language Processing.

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[ReubenPeter]

From this video I learnt about count vectorization and about its implementation. Thank you

[muskanmahajan]

In this video I have learnt about count vectorization, this course is very easy to understand and easy to implement.

[viveklearningg]

In this video of Natural Language Processing, we learned about the basics of Count Vectorization in NLP.

[veenab.s]

In this session learnt about vectorization, working of vectorization, count vectorization in NLP.
Thank you

[nandanasreeraj]

I learnt about count vectoristion and how it works...Thanks for the awesome video

[jaisonj]

Learnt about count vectorization in NLP. The course is good and easy to understand

[vaibhavchawla]

Learnt about applying count vectorizer on text.

[soumyadarshan]

From this video I learnt about count vectorization and about its implementation.

[naveenkumarn]

Learnt:
What is Vectorization.
How vectorization works.
Implementation of countvectorier for sample data and it's ouput.
Thank you.

[sanjeevjoshi]

Key learnings
Know-how of vectorization in NLP
Usage and working of count vectorization
Implementation of count vectorization using sklearn library

[anuragkumarsingh]

In this video of Natural Language Processing, we learned about the basics of Count Vectorization in NLP

[indraneeldhavale]

In this session I have learnt what is vectorization
Usage and working of count vectorization
and its implementation

[KhushiSingh-xvpo]

In this session I learnt about:
* vectorization
* import it count vector from sklearn
*analyzer
*how we used count vectorization that represents the count of words occurred in a sentence

[mylifeasJoT]

I have learnt about sklearn and import CountVectorizer, about analyzer and fit transform

[kashishmittal]

In this lecture we learnt:
1.what is count vectorization
2.sklearn library is required for count vectorization
3.count vectorization is used to get the frequency of a word in a sentence.
4.vectorization is a process of converting a text into number

[snehakulkarni]

In this video I've learnt about vectorization meaning and why it's used with an example, vectorizer using count vectorization, sklearn class usage fit_transform() meaning and vectorization representation. Overall thank u

[shamshun]

Learned how to remove punctuation's, tokenize, remove stopwords and applying CountVectorizer

[AbhishekGupta-zfsw]

Great Video, learned about the concept behind the count vectorization and implemented it using sklearn library

[himaniag]

Vectorization :
* m/c doesn't understand text data so we have transform it into integers.
* there are many types of vectorizers as

* count :
- Count Vectorizer works on Terms Frequency.
- it creates a document-term matrix where the entry of each cell will be a count of the numbers of times that word occured in that document.

* TF
* IDF

[kanchansharma]

In this video, I learnt
What is count vectorization in NLP
Working of vectorization