And this is the earliest data that I can find.

Most of them have fairly good education.

The contrast in literacy rates is especially sharp between Chinese women and Indian women.

Adult literacy amongst the proletariat has risen by 56 per cent.

Secondly, the literacy rate in Europe of that time was low.

And they invested in social programs health and education.

Just think of the benefits when it comes to jobs, productivity, employment, child nutrition, maternal mortality, literacy and much, much more.

In a way 50 percent of performance is good, but it's not so good when we compare to what we can do in handwriting recognition.

Optical Character Recognition

In China, there is a large number of characters, so the goal of the character simplification was to replace the complex traditional characters with easy to remember simplified characters and increase the literacy rate.

Pi's just a number.

Here I have my solution.

Optical Character Recognition

I haven't told you about the definition of literacy.

format character

We often call them identifiers because they identify a particular value or storage location.

Ralph is one identifier.

And this was a challenge now thrown open to the entire computer vision community.

Incidence Unique string identifier

So the call to action in this video was to stand up for their rights and ask for the land.

If you think back to our lexer rule for identifiers, it looks something like this.

Your Majesty has indeed committed an indiscretion.

Lata, l a t a, is definitely an identifier using our previous rules.

That is very bad!

Spellchecking does not recognize non English characters.

Set here the strings that identify content that recurs.

That's totally allowed in the identifier, but we'll say not at the beginning.

We had knowledge about the electromechanical efficiency and then we can calculate the aerodynamic efficiency.

How much money are you spending per month?

Once I tried to calculate them, but they're astronomical.

After that, it can be as long as we want, and it can have as many underscores as we want and then letters as well where the casing doesn't matter.

How many examples were used? So, for now you can focus on just one vertical column corresponding to fifteen training examples.

Remember everything we get from we get in our web app is going to be strings.

Here's a quiz to make sure you understand how to calculate these probabilistic models.

So 16 was significantly better than chance.

And this is from Delhi.

And then you get that wonderful effect when we got female literacy one generation later.

literally I'm just saying if you divide the circumference by the diameter, you're going to get pi.

And remember that substring inclusion starts at 1 and goes up to, but not including, the negative 1.

There are 2D problems. Fundamentally 2D problems such as handwriting recognition or face detection.

Tell me the probability of the whole string woe is me at the beginning of a sentence given that we're starting at the beginning of a sentence and put your answer in here.

He had to learn to hear the music in language.

So that it can understand what's in the book.

Now let's take a step back for a second, and I'm going to talk about probabilistic letter models.

But it turns out I can also do it just by looking at letter sequences, the frequency of of single letters or pairs of letters or triplets of letters.