I want to write this every time when I go through your RU-vid videos (earlier Deep Leaning and now NLP).... You are an outstanding educator. Your practice of illustrating complex concepts with pertinent use cases adds an engaging dimension to the learning experience. Your proficiency in simplifying intricate ideas with clarity is truly remarkable. Your sense of timing in presenting crucial details is impeccable, and your suggested reading resources are exceptionally valuable. Thank you for putting your efforts in creating such useful leaning material.
You are the best Dhaval. I have seen many tutorials on different ML/DL/NLP topics but the way you teach is something different. It is very hands on and easy to understand. I really look forward to your videos. I recently did post graduate program in Data Science from Great Lakes but frankly, the teaching you provide is much better than some of the professors I had there. Keep it up!
Good intro into NLP concepts, Dhawal. Btw, as someone who has worked on a large scale NLP projects here in Toronto, I can vouch that FirstLanguage NLP APIs are right up there with one of the biggest cloud service providers' speech SDK - and at a fraction of cost! And the co-founder is a PhD specializing in NLP herself.
Yup, indeed the co founder is quite knowledgeable and the platform is also very well built. I suggest people to try it out, it saves you a lot of money 💵
Indeed it's a very good playlist on NLP, but can u please do some hands-on experience on audio files also. i mean if u can help me with the audio files instead of text as a data set,
00:02 Tokenization is the process of splitting text into meaningful segments. 02:21 Tokenization in Spacy 07:22 Spacy's tokenization splits currency and punctuation into separate tokens 09:39 Tokenization in Spacy involves splitting text into separate tokens based on prefixes, suffixes, and exceptions. 14:48 Tokenization in Spacy allows for the identification and classification of different attributes of tokens. 17:19 Tokenization in Spacy 21:52 The main point of the given subpart is to explore the attributes of spaCy tokens. 24:17 Tokenization in Spacy allows you to type in different languages even with an English keyboard 29:02 Tokenization in Spacy allows splitting the text into segments 31:13 Tokenization is an essential part of the spaCy pipeline. 35:20 Tokenization in Spacy
You make wonderful videos! 👏 I have a quick question: 🤷♂️ I have a set of words 🤷♂️. (behave today finger ski upon boy assault summer exhaust beauty stereo over). How do I use this? 🤨
The referred book at page vi: "If you have never studied statistics, I think this book is a good place to start. And if you have taken a traditional statistics class, I hope this book will help repair the damage." 😄
Hello Dhaval, Do you have any tutorial on Spiking nueral network, or guide that could help. By the i have following you awesome tutorials on Nueral networks, thanks a million
@@ChildhoodSaverIndia does not has any national language it was 22 official languages and 2 administrative languages hindi and English. Hindi is not our national language
answer of exercise question 2 is little wrong for cases like " i have 500 $ and the quantity of good people in the company is 10" This is correct: # Extract money transactions = "Tony gave two $ to Peter, Bruce gave 500 € to Steve 10" doc= nlp(transactions) ans= [] count= len(doc) for token in doc: if token.i != count-1: if token.like_num and doc[token.i + 1].is_currency: ans.append(token.text + ' '+ doc[token.i + 1].text) ans
