Deep learning refers to neural networks that are much deeper than the three to four layers people were using before. It's interesting because, in order to make it practical at all, you have to use a pretraining step which involves pretending that it's a totally different thing called a restricted Boltzmann machine. That pretraining, if you're lucky, acts as a form of feature extraction and can save feature engineering time.
The initial successes seemed almost magical and everyone leapt on it. It turned out that those successes were very specialized and, while it's a really useful tool, it's not the panacea people thought it might be.
You can say Deep learning is the next evolution of machine learning – it’s how machines can make their own accurate decisions without a programmer telling them so.
The types which I have explained in the post are different learning methods which we can use depending on our requirement. If the data is labelled then supervised else unsupervised.
A deep learning model is able to learn through its own method of computing – its own “brain". And for this it uses a layered structure of algorithms called an artificial neural network (ANN).
Nice 👌 post
Can you please tell me where does Deep Learning fits into the above 3 categories of machine learning ?
Deep learning refers to neural networks that are much deeper than the three to four layers people were using before. It's interesting because, in order to make it practical at all, you have to use a pretraining step which involves pretending that it's a totally different thing called a restricted Boltzmann machine. That pretraining, if you're lucky, acts as a form of feature extraction and can save feature engineering time.
The initial successes seemed almost magical and everyone leapt on it. It turned out that those successes were very specialized and, while it's a really useful tool, it's not the panacea people thought it might be.
You can say Deep learning is the next evolution of machine learning – it’s how machines can make their own accurate decisions without a programmer telling them so.
The types which I have explained in the post are different learning methods which we can use depending on our requirement. If the data is labelled then supervised else unsupervised.
A deep learning model is able to learn through its own method of computing – its own “brain". And for this it uses a layered structure of algorithms called an artificial neural network (ANN).
Ohhh 😲🤤🤤
Well i guess Deep Learning is lit af🔥🔥
Looking forward for your new posts 😀