Hi everyone. I am excited to see you on board,
and welcome to our course.
I want to start our lesson with the informal discussion of who we are,
and who is this course for.
Then, we will have a brief introduction to the area of Natural Language Processing.
You know, it might feel a little hand wavy as any introduction actually,
but I hope that after our course,
you will know exactly everything that will be mentioned in our lesson now.
So, ready? Let us get started.
My name is Anna, and we have a big nice team creating the course for you.
So, we have Sergey, Alexey, Andrey,
and one more Anna preparing the materials.
I have a background on computer science and machine learning,
and I'm now applying this background in natural language processing in different ways.
And you know these different activities like research, teaching,
and industry, you've had different perspectives to the same area.
So, for example, when you come to the industry very soon,
you realize that not a new paper from academia is useful in the particular settings,
like large scale implementation or some noisy dater or specific needs of your business.
So, probably, you need to build
some more simple solution but that would work nicely in your specific settings.
Okay. Now, who is this course for?
When I was thinking about what would be one word to characterize our audience,
I thought that it would be the word curious.
So, this course is for curious people who want to know what is inside some applications.
For example, you have differently used machine translation.
Do you know how it works or
dialogue agents that are so popular nowadays? What is inside there?
And you know, this popularity of certain applications is couldn't bet.
So, for example, for dialogue agents,
we have so much hype around so that it is not
that easy to distinguish what is just some beautiful words,
and what is something that will really work in practice.
So, hopefully, one outcome of our course for you would be
the ability to distinguish between the hype and something that really works.
Now, our course is rather in-depth.
So, I want to go with some details through several methods in NLP
because these will give you the ability to distinguish the hype from the methods.
Okay? Also, we will cover
real state-of-the-art approaches both in research and production.
And as I have already said,
this could be rather different approaches.
Now, another goal that's a little bit contradict to
going in-depth would be to have a big picture of the area.
So, I feel like it is really important to have some expertise like,
I am given a task, what should I do with it?
What approaches would work in this certain case?
To have this intuition,
we will try to discuss as many different settings and tasks as possible,
and cover some approaches for them.
And obviously, we should not only talk and you should not only listen and read about it,
but you have to do some practice to get a hands-on experience.
So, we are preparing materials for you for home assignments in
Python for some popular NLP tasks like text classification,
or duplicate detection, named entity recognition,
and some others, so that you have some experience with your own hands.
Also, this home tasks will help you to build
the project of our course that would be a conversational chat-bot.
So now, I feel like it is really important also to see what is our course not about,
because NLP is so big that obviously our course cannot feed everyone's needs.
So, I feel like if you only want to know
some black box implementations and stock them together to build some solution,
then probably, this course is not for you.
Also, I think that it is a good idea to take machine learning and
deep learning courses first to fill it is with some names and formulas.
For example here, I have a quick test for you.
Do you know what is Recurrent Neural Networks?
Or have you heard about likelihood maximization?
Just take a moment to see how comfortable you are with
these words and see whether you need to take,
for example, deep learning course in
our specialization first before going to this course.
Also, we expect that you have some experience with Python.
Probably, you don't have any experience with TensorFlow,
and this is maybe okay,
and then this is a good moment for you to try to go through some tutorials,
and this course could be a good reason to go through them.
Actually, TensorFlow has really nice tutorials,
so I think that it shouldn't be a problem for you.
I hope you are still not frightened.
And I hope you are ready for our journey to the NLP.
And I want to start this journey with the survey of the main approaches.