NLP history up to RNN| Natural language processing in artificial intelligence | NLP course

NLP history up to RNN| Natural language processing in artificial intelligence | NLP course
#nlp #deeplearning #machinelearning

Hello,
My name is Aman and I am a Data Scientist.

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[nanyongaaziidah]

the best teacher ever, You're teaching in a very simple and easily understandable. thanks alot

[nagasudha]

Perfect teacher and ur lecture matches all inteligence levels

[rajeevmishra]

you got your trainable params as 24 in this way :
trainable params = (vocab words * dimensions)
in your case, vocab words = (n + 1, n = no. of unique words)
dimensions = 3.
so, you have 8 * 3 = 24 trainable params

[naveenmurugan]

You are teaching in a very simple and easily understandable, you became my favorite Youtube channel for Data Science. Keep making content like this, Thank you.

[mayanklohani]

Following u from last 6 months. You are a gem ❤ Cracked 3 interviews following ur videos.

[dharmaraj]

Excellent and easily understandable explanations. waiting for your videos on attention mechanism and LLM. Requesting you to please make a video on how to utilize pretrained models on LLM

[vijayaselva]

Very detailed explanation. Thank you so much Guruji!

[shashankbarai]

Heads off to you again, m already your Fan....!

[samadhanpawar]

7 inputs * 3 output = 21 + 3 outpus bias = 24

[salomishiny]

Understanding the Natural Languaging sir.

[mukulkulshreshtha]

please upload videos for image classification CNN also .very much needed.

[muhammedthayyib]

Number of units in the input layer is 8
Number of units in the output layer is 3

Total number of trainable parameters in 8*3=24 (Since it is a Dense)

[ksaha]

Exactly the kind of video I was searching for past 2 weeks.. He knows his market and TG 😂😂

[SantoshKumar-jwhw]

You are awesome man. Loved this video.

[tejkiran]

Hi aman thanks for the video.. I saw the video unfold RNN while I was in office.. I thought i can watch once i back home..Is that deleted? Will you upload it later?

[c.nbhaskar]

Hi aman, i am waiting for a video on Attention mechanism and transformers in an easily understandable way .I have searched many channels, but could not find it