- [Ronnie] This is Ronnie Sheer.
I wanted to thank you for coming along
for this course and exploring AI
by removing a lot of the commonly used tools and libraries
and implementing things from scratch.
Moving forward, there are a few courses
and resources I encourage you to check out.
The first one being "Training Neural Networks
in Python" by Eduardo Corpeno.
Now, we haven't really touched on neural networks
in this course, and they're really integral part
of modern artificial intelligence and machine learning.
There's also my course, "Introduction to Prompt Engineering
for Generative AI."
And in that course, we both look at techniques
for prompt engineering, like few-shot learning
and we also look at the landscape
of generative AI by generating different images and texts.
It's very hands-on and lots of fun.
I also encourage you
to check out Jonathan Fernandes's course,
"Transformers: Text Classification for NLP Using BERT."
This course really relates to the last chapter
of this course, and it looks at how you can use transformers
for text classification tasks, which can range
from sentiment analysis and matching similarity.
Now, as far as tools and resources,
I encourage you to check out Hugging Face.
It's a hub for pretty much all things AI
and machine learning these days.
There's also OpenAI's APIs,
which you can use to build some really cool stuff
and there's another company called Cohere,
which has an NLP toolkit as a service.
So once again, thank you so, so much for coming along
and always be learning.