Top Applications of Machine Learning in 2021

Top 10 Applications of Machine Learning in 2021
Top Applications of Machine Learning in 2021

Machine Learning has improved our lives in a number of wonderful ways. Today, let’s talk about some of these, and these are the top 10 applications of machine learning .

1. virtual personal assistants

Google Assistant, Alexa Cortana, and Siri, Now we’ve all used one of these, at least at some point in our lives.

Now these help improve our lives in a great number of ways. For example, you could tell them to call someone, you could tell them to play some music, you could tell them to even sheduled an appointment.

So how do these things actually work? First, they record what you’re saying, send it over to a server, which is usually in a cloud, decoded with the help of machine learning and neural networks, and then provide you with an output.

So if you ever notice that these systems don’t work very well, without the internet, that’s because the server couldn’t be contacted.

2. Social media personalization.

I want to buy a DJ, and I’m on Amazon, the thing is, i don’t have money, so I don’t want to buy it right now. But the next time I’m on Facebook, I’ll see an advertisement for the product.

Next time I’m on YouTube, I see an advertisement. Even on Instagram, I see an advertisement. So here with the help of machine learning,

Google is understood that I’m interested in this particular product, hence, it’s targeting me with these advertisements.

3. Email spam filtering

Now how does Gmail know what spam and what’s not spam? So Gmail has an intact collection of emails, which have already been labeled as spam or not spam.

So after analyzing this data, Gmail is able to find some characteristics like the word lottery or winner.

From then on. Any new email that comes to your inbox goes through a few spam filters to decide whether it’s spam or not. Now some of the popular spam filters that Gmail uses is content filters, header filters, General blacklist filters, and so on.

4. Online fraud detection

Now there are several ways that online fraud can take place. For example, there’s identity theft, where they steal your identity fake accounts,

where these accounts only lasts for how long the transaction takes place and stop existing after that and man in the middle attacks where they steal your money while the transaction is taking place.

The feed forward neural network helps determine whether a transaction is genuine or fraudulent. So what happens with feed forward neural networks are that the outputs are converted into hash values and these values become the inputs for the next round.

So for every real transaction that takes place this specific pattern a fraudulent transaction would stand out because of the significant changes that it would cause with the hash values.

5. Stock market trading

Machine learning is used extensively when it comes to stock market trading. Now you have stock market indices like MCI they use long short term memory neural networks.

Now, these are used to classify process and predict data when there are time lags of unknown size and duration. Now this is used to predict stock market trends,

6. Assisted medical technology.

Now medical technology has been innovated with the help of machine learning. diagnosing diseases has been easier from which we can create 3d models that can predict where exactly there are lesions in the brain.

It works just as well for brain tumors and ischemic stroke lesions. They can also be used in fetal imaging and cardiac analysis.

Now some of the medical fields that machine learning will help assist in is disease identification, personalized treatment, drug discovery, clinical research, and radiology.

7. Automatic translation

No, say you’re in a foreign country and you see billboards and signs that you don’t understand. That’s where automatic translation comes of help.

Now, how does automatic translation actually work? the technology behind it is the same as the sequences sequence learning, which is the same thing that’s used with chatbots.

Here the image recognition happens using convolutional neural networks and the text is identified using optical character recognition.

Furthermore, the sequences sequence algorithm is also used to translate the text from one language to the other.

And that brings us to To the end of this article I hope you guys found this article helpful and informative. Thank you for watching

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