C Programming for Machine Learning (LIVE)

C Programming for Machine Learning (LIVE)



The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we’ll do this together using Google Colab in the browser. Join me, there’s a lot to cover here!

Code for this video:

Please Subscribe! And like. And comment. That’s what keeps me going.

Want more education? Connect with me here:
Twitter:
Facebook:
instagram:

This video is apart of my Machine Learning Journey course:

More learning resources:

Join us in the Wizards Slack channel:

Learn more about the School of AI:

And please support me on Patreon:

Signup for my newsletter for exciting updates in the field of AI:

Hit the Join button above to sign up to become a member of my channel for access to exclusive content!

#Programming #Machine #Learning #LIVE

learn c programming

cython,C++,python,C programming,programming,natural language processing,siraj raval,live stream,machine learning,deep learning,text analytics,tokenization,part of speech tagging,word2vec,NLP,AI,artificial intelligence,live programming

Leave a Reply