Complete Natural Language Processing (NLP) Tutorial in Python! (with examples)

In this video we go through the major concepts in natural language processing using Python libraries! We use examples to help drill down the concepts. There is content in this video for all skill levels (beginners to experts). I originally recorded this video for the PyCon Conference.

Some of the topics we cover:
- Bag-of-words
- Word vectors
- Stemming/Lemmatization
- Spell correction
- Transformer Architecture (Attention is all you need)
- State of the art models (OpenAI GPT, BERT)

Some of the libraries used:
- sklearn
- spaCy
- NLTK
- TextBlob

Hope you enjoy & let me know if you have any questions! Make sure to subscribe if you haven't already :).

-------------------------
Follow me on social media!

Practice your Python Pandas data science skills with problems on StrataScratch!

Join the Python Army to get access to perks!

*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

-------------------------
Song at the end
Creative Commons — Attribution 3.0 Unported — CC BY 3.0

-------------------------
Video Timeline!

~~ NLP Fundamentals ~~
0:00 - Announcements!
1:12 - Video overview & timeline
3:06 - Bag of words (BOW) overview
4:42 - Bag of words example code! (sklearn | CountVectorizer, fit_transform)
11:20 - Building a text classification model using bag-of-words (SVM)
14:07 - Predicting new utterances classes using our model (transform)
16:02 - Unigram, bigram, ngrams (using consecutive words in your model)
19:28 - Word vectors overview
23:27 - Word vectors example code! (Using spaCy library)
28:10 - Building a text classification model using word vectors
34:04 - Predicting new utterances using our model

~~ Miscellaneous NLP Techniques ~~
40:42 - Regexes (pattern matching) in Python.
52:30 - Stemming/Lemmatization in Python (text normalization w/ NLTK library)
1:01:17 - Stopwords Removal (removing most common words from sentences)
1:05:56 - Various other techniques (spell correction, sentiment analysis, part-of-speech tagging).

~~ State-of-the-art Models ~~
1:12:45 - Recurrent Neural Networks (RNNs) for text classification
1:17:00 - Transformer architectures (attention is all you need)
1:21:00 - Writing Python code to leverage transformers (BERT | spacy-transformers)
1:25:00 - Writing a classification model using transformers/BERT
1:29:37 - Fine-tuning transformer models
1:31:16 - Bring it all together and build a high performance model to classify the categories of Amazon reviews!

[KeithGalli]

I created a second channel where I post more Python content, check it out! 😊

[lakshyashrungarpure]

I got a job because of your tutorials!! Thanks Keith🤩

[pawan-deow]

Glad to have you back and making awesome tutorials. Have learnt alot from you.

[francis]

Great to see you back Keith. Wishing you all the best in your recovery.

[alan]

Bookmarking this and will watch it in the morning.

[vhana]

Finally, you came back. I liked your explanation.

[zulekhaimtiaz]

Heyy Keith!! I just want to thank you sooo much. I applied for an internship which required for me to submit an assignment on data classification and your SKLearn video helped me soo much with the task! I really am so grateful to you! Your tutorials are the best!

[Amulya]

This is a great introductory tutorial on NLP. Perfect for a newbie

[avixek]

You are probably one of the smartest guy on youtube. Keep making your videos. You are doing God's work!!!

[amansorout.]

Damn, I am very happy you are back bro. 😀

[bosszz]

I've been following your tutorials, but I've been busy with object detection lately, so I'll be watching this nlp video of yours later

[shivamsahu]

Thank you, Keith. Your session helped me a lot.

[richarddankwah]

Glad to See this Mr. Keith. Always impressive and fun. Thank you very much. But am your big fun as well

[RichardHarrowz]

LOVE TO SEE YOU AGAIN MAN! LOVE THE CONTENT AND HOW U EXPLAIN!!!!

[muhammadzakiahmad]

Amazing tutorial Mr.Keith, I just wanted to have a know how of NLP and this tutorial was perfect for it.

[nazrulxh]

great tutorial brother. Highly appreciated

[wahaha]

hi Keith, great video. You provide an one-stop service, hhh. Great!

[codewithkarthik]

It would be super nice if you would make a text generation video. As always loved the vid keith

[DJdopeMike]

Thank you for the great overview of NLP!

[christianondo]

great tutorial, thanks so much for putting this out there. It's pretty crazy how easy it is to learn stuff if you're willing to search youtube