Damn, you're always learning. I come back to this channel thinking "I might have finally got to your level of programming" to find you're way ahead of me in AI and ML now... Oh well, very impressive! I have sort of a one-sided competition with you in my head.
This was a great intro to naive Bayes! I first encountered the idea in the book "The Master Algorithm" by Pedro Domingos. It's a great read and covers five main groups in machine learning, one of which being composed of the Bayesians :-) check it out at your local library, that's where I found it. Thanks for these videos! Looking forward to the next.
Hey, it's a really nice and intuitive explanation about the Bayes classifiers. I also like the kind of demos that you show, and as I learnt from your GitHub, I think you are also a web developer, which explains all those cool demos :). Could you tell me what tools do you use for making these demos? I'm not at all familiar with Go, so I couldn't go through a major part of your GitHub repository.
It's over a year, but if you are still coding, I hope you learned a very important lesson: don't do this. Don't just ask for code, show something that you tried and eventually failed and how you are stuck. By showing even a little bit of effort you encourage someone to give you advice, with two benefits: you will have more chances attracting good answers and you will learn the solution better than if it was just spoonfed to you. Besides, the technique described here is very easy to implement, probably the most difficult thing is to break up a sentence into words and acquiring good data to start with.
Damn, you're always learning. I come back to this channel thinking "I might have finally got to your level of programming" to find you're way ahead of me in AI and ML now... Oh well, very impressive! I have sort of a one-sided competition with you in my head.
Haha, a little healthy competition is always a good thing. :)
This was a great intro to naive Bayes! I first encountered the idea in the book "The Master Algorithm" by Pedro Domingos. It's a great read and covers five main groups in machine learning, one of which being composed of the Bayesians :-) check it out at your local library, that's where I found it. Thanks for these videos! Looking forward to the next.
I watched a couple of videos of this guy. This guy is awesome.
Glad I learned to implement a bayes classiefier!
Where did you get the dataset at to train the classifier? Did you make it yourself?
Hey, it's a really nice and intuitive explanation about the Bayes classifiers. I also like the kind of demos that you show, and as I learnt from your GitHub, I think you are also a web developer, which explains all those cool demos :). Could you tell me what tools do you use for making these demos?
I'm not at all familiar with Go, so I couldn't go through a major part of your GitHub repository.
You are my inspiration!
hello dear i need code of this program / algo... i need implementation
It's over a year, but if you are still coding, I hope you learned a very important lesson: don't do this. Don't just ask for code, show something that you tried and eventually failed and how you are stuck.
By showing even a little bit of effort you encourage someone to give you advice, with two benefits: you will have more chances attracting good answers and you will learn the solution better than if it was just spoonfed to you.
Besides, the technique described here is very easy to implement, probably the most difficult thing is to break up a sentence into words and acquiring good data to start with.
Can u send me the code of this text classifier
Bro post full sentiment analysis video on web application if you can.
sir ,
please start a course where we can learn such Algorithm easy and rapidly it will help us very much please
please provide this code in python.
Great Explaining. I'm 15.
very easy concept
marry me ;)