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Love her voice, it's so pleasant and so much clarity in explaining the concepts! I would pay to hear your voice all day lol. Thank you, finally found the best video to grasp these concepts. :)
Hello, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
Thank you for choosing us as your learning partner. We are thrilled to hear that you enjoyed your experience with us! If you are looking to expand your knowledge further, we invite you to explore our other courses in the description box.
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Hey, thank you for appreciating our work. We are glad to have helped. Do check out our other tutorial videos and subscribe to us to stay connected. Cheers :)
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Thanks it was really helpful to understand what type of data I'm working on .. just to confirm . Are football datasets are unsupervised on common basis or not ?.
Hi Tapesh, if you are trying to predict the performance of a club or a team in a football dataset or if you are predicting each player's performance in a match or a group of matches, these are examples of supervised learning.
Hi simplilearn! I have a doubt. I would love if you help me clear it. In classification(supervised learning), we use discrete values and we classify the data to be either 1 or 0 and True or false. But can we take multiple discrete values? like we can classify it in more than two classifications? Like if we say 1 or 0 or -1? I am confused. Plz help me out with a clear explanation. I hope I am clear with my question.
"Hi , You can definitely use supervised classification algorithms to create multi-class classifier models. Please refer to this documentation by ScikitLearn to learn more scikit-learn.org/stable/modules/multiclass.html"
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6 лет назад+1
Are you going to give all machine learning tutorials on RUclips or would be premium. Version on your website?
Hi Darshan, thanks for checking out our tutorial. We are not going to publish all the machine learning videos on RUclips. More advanced and depth contents are available in premium only. If you are interested in signing up for the machine learning course, check this link: www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course
No, Deep Learning is not same as Unsupervised Learning. In unsupervised learning, there is no labelled data for both independent and dependent variables. K-Means Clustering is a popular example to unsupervised learning. Deep Learning is a broader category in Machine Learning that uses neural nets to perform prediction tasks. It uses both structured and unstructured data.
unsupervised learning should have feedback mechanism as it records the history of previous customers and recommends the customer 3 to buy.Is this correct?
In ML we don't really write precise steps for the computer like in normal programming. Instead we try to give the computers a dataset from which to learn from.That's what "not explicitly programmed" means. Hope that Helps
"Hi Tanoy, If you are working on a supervised classification problems or unsupervised clustering problems, then you would need at least one qualitative variable. But, for a regression problem, your target variable should be quantitative."
I'm very sorry I could be a little racist to tell that but until know when I here an Indian English speaker that try to explain something I was directly closing the video because of that accent but this is the fisrt time I thought the sound is cute, clear and can totally understandable. Thank you very much for that.
You mentioned fraud detection as a case of unsupervised learning in first video of this series and now in this video it is mentioned as a case of supervised learning
Fraud detection in Machine Learning belongs to the category of Anomaly detection. There are 3 types of anomaly detection - supervised, unsupervised and semi-supervised anomaly detection.
Fraud detection can be carried out using both supervised and unsupervised learning algorithms. It depends on the type of fraud you are trying to detect. In supervised learning, a random sub-sample of all records is taken and manually classified as either fraudulent or non-fraudulent. Unsupervised methods don't make use of labelled records. Bolt and Hand uses Peer Group Analysis and Break Point Analysis to analyze the spending behavior in credit card accounts. Pattern recognition algorithms can be used to match fraud patterns. Supervised neural nets can also be used to learn suspicious patterns from samples.
You are awesome nigga , I watched about 15-20 videos for better explanation of unsupervised, lately found you.. the way you expound it just got fit into my thick skull... thanks mann... you tooo good apeksha ...
Hi Vinay, we appreciate your kind comment. We will definitely send your regards to Apeksha. Do show your love and support by subscribing to our channel and also giving a thumbs up to our videos. Cheers!
"🔥Caltech Post Graduate Program In AI And Machine Learning - www.simplilearn.com/artificial-intelligence-masters-program-training-course?E5QZ8G_78c&Comments&RUclips
🔥IITK - Professional Certificate Course in Generative AI and Machine Learning (India Only) - www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?E5QZ8G_78c&Comments&RUclips
🔥Purdue - Post Graduate Program in AI and Machine Learning - www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?E5QZ8G_78c&Comments&RUclips
🔥IITG - Professional Certificate Program in Generative AI and Machine Learning (India Only) - www.simplilearn.com/iitg-generative-ai-machine-learning-program?E5QZ8G_78c&Comments&RUclips
🔥Caltech - AI & Machine Learning Bootcamp (US Only) - www.simplilearn.com/ai-machine-learning-bootcamp?E5QZ8G_78c&Comments&RUclips"
Thanks a lot. I had bit confusion between supervised and unsupervised. Now it's cleared.
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fariha.csraxis@gmail.com
Wanting the career guide 🤞🏻❤️
Love her voice, it's so pleasant and so much clarity in explaining the concepts! I would pay to hear your voice all day lol. Thank you, finally found the best video to grasp these concepts. :)
Wow, thank you!
I have a doubt in regression and classification before watching this video. Now it's clear. Thank you Simplilearn
Glad to hear that
Today my exam and your video help me to cover my topic quickly .
Please make more and more informative video.
Thank you so much
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Wow....Great explanation....U provided me a clear picture of supervised and unsupervised learning.....Thanks a lot....👏👏👏
Glad to hear that! Thank your for watching!
Very clearly explained with real time examples. Easier to understand!
Glad it was helpful!
excellent. Best video I've found explaining this
Thank you for choosing us as your learning partner. We are thrilled to hear that you enjoyed your experience with us! If you are looking to expand your knowledge further, we invite you to explore our other courses in the description box.
Excellent voice.., this gives me more interest to listen and clear explanation of basic content. thank you
Hi, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
Superb vedio which helps me a lot
Happy to help
I like it
It explains everything clearly
May God accept your efforts
Hi Anjuman, thanks for watching our video. We have sent the requested dataset to your mail ID. Do show your love by subscribing to our channel using this link: ruclips.net/user/Simplilearn and don't forget to hit the like button as well. Cheers!
Very very good. Very helpful in my exams . I got good marks .thanks
We're happy for you! Thank you for watching!
@@SimplilearnOfficial I am also happy because you replied
ppt is best and you explanation is awesome
Thank you so much 😀
I loved your Presentation !Thanks a lot!
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what a great and helpful presentation.much appreciated.
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Simply superb,,, very cool and clear presentation... 👌🤝
Thank you so much 👍
Thank you Subeksha, Well explained , you made it easy to understand basic concept of supervised & unsupervised learning !!!
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video is understandable . And with real life examples
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Best source for ML 💥
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very clear presentation thank you !
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Really excellent lecture! Thanks a lot!
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Best explanation I’ve had heard
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you're the best. Thank You!
Thanks for the kind compliment! Cheers!
Really you made it simple and to the point learning...
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Very Informative video, Thanks
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voice is very beautiful
Thanks for the kind comment! Cheers!
thank you sister !
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This type of teachers I want in my life not the ones I am getting in my college...
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nice explanation
Thanks and welcome
super i saw so many videos it is best
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Mam, you have very good way to teach, do you have complete course vedio for machine learning?
Yes, you can check out the Machine Learning full course video using this link: ruclips.net/video/9f-GarcDY58/видео.html
amazing explanation
Glad you think so! Thank you for watching!
Thanks man for such a nice video
Our pleasure!
most valuable content... thank you so much
Glad you think so! Do subscribe to our channel and stay tuned.
nice info, thanks
Glad it was helpful! Thank you for watching!
Thanks it was really helpful to understand what type of data I'm working on .. just to confirm . Are football datasets are unsupervised on common basis or not ?.
Hi Tapesh, if you are trying to predict the performance of a club or a team in a football dataset or if you are predicting each player's performance in a match or a group of matches, these are examples of supervised learning.
Superb ma
Glad you enjoyed it! Thank you for watching!
Perfect👌
Hi simplilearn!
I have a doubt. I would love if you help me clear it.
In classification(supervised learning), we use discrete values and we classify the data to be either 1 or 0 and True or false. But can we take multiple discrete values? like we can classify it in more than two classifications? Like if we say 1 or 0 or -1? I am confused. Plz help me out with a clear explanation. I hope I am clear with my question.
"Hi ,
You can definitely use supervised classification algorithms to create multi-class classifier models. Please refer to this documentation by ScikitLearn to learn more scikit-learn.org/stable/modules/multiclass.html"
@@SimplilearnOfficial thanku soo much simplilearn😇
Really a nice 1..it helped me a lot
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superb explanation!
Hi Salitha, we appreciate the kind comment! enjoy!
@@SimplilearnOfficial awesome and simple explanations...keep it up!
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Very well explain I like it
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Thank you very much for that well done video :)
Hi,
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i like your voice and subject content too
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Are you going to give all machine learning tutorials on RUclips or would be premium. Version on your website?
Hi Darshan, thanks for checking out our tutorial. We are not going to publish all the machine learning videos on RUclips. More advanced and depth contents are available in premium only. If you are interested in signing up for the machine learning course, check this link: www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course
Very well explain
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Nice voice
Thanks for watching our video. Cheers!
Thank you!
Very welcome! Do subscribe to our channel and stay updated.
Nice video. I have a question. Is deep learning same as unsupervised learning?
No, Deep Learning is not same as Unsupervised Learning. In unsupervised learning, there is no labelled data for both independent and dependent variables. K-Means Clustering is a popular example to unsupervised learning. Deep Learning is a broader category in Machine Learning that uses neural nets to perform prediction tasks. It uses both structured and unstructured data.
Great!
Thanks for the kind comment. Cheers!
Great
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unsupervised learning should have feedback mechanism as it records the history of previous customers and recommends the customer 3 to buy.Is this correct?
"Hi
The feedback mechanism is for reinforcement learning algorithms. Unsupervised learning works with unlabeled data."
I love the voice....
Hi Rahul, thanks for the kind comment. We will certainly inform this to our instructor. Cheers!
Nice1
Thanks! Check out ruclips.net/video/ukzFI9rgwfU/видео.html to dive in deeper! :)
Hi, what do you mean by without being explicitly programed in machine learning definition
In ML we don't really write precise steps for the computer like in normal programming. Instead we try to give the computers a dataset from which to learn from.That's what "not explicitly programmed" means.
Hope that Helps
I want to know the algorithms also. Please make a vedio on that also
Hi Prachi, we have made a exclusive video on Machine Learning algorithms: ruclips.net/video/I7NrVwm3apg/видео.html.
Is recommendation system an unsupervised learning association one??
Recommendation system uses both supervised and unsupervised learning.
can the both models supervised and unsupervised learning needs at least one quantitative feature or qualitative feature or both
"Hi Tanoy,
If you are working on a supervised classification problems or unsupervised clustering problems, then you would need at least one qualitative variable. But, for a regression problem, your target variable should be quantitative."
I'm very sorry I could be a little racist to tell that but until know when I here an Indian English speaker that try to explain something I was directly closing the video because of that accent but this is the fisrt time I thought the sound is cute, clear and can totally understandable. Thank you very much for that.
Hey, thank you for watching our video and for the honest feedback. We appreciate it. Do subscribe, like and share to stay connected with us. Cheers :)
You mentioned fraud detection as a case of unsupervised learning in first video of this series and now in this video it is mentioned as a case of supervised learning
Fraud detection in Machine Learning belongs to the category of Anomaly detection. There are 3 types of anomaly detection - supervised, unsupervised and semi-supervised anomaly detection.
@@SimplilearnOfficial do you mind explaining it in more detail.
Fraud detection can be carried out using both supervised and unsupervised learning algorithms. It depends on the type of fraud you are trying to detect. In supervised learning, a random sub-sample of all records is taken and manually classified as either fraudulent or non-fraudulent. Unsupervised methods don't make use of labelled records. Bolt and Hand uses Peer Group Analysis and Break Point Analysis to analyze the spending behavior in credit card accounts. Pattern recognition algorithms can be used to match fraud patterns. Supervised neural nets can also be used to learn suspicious patterns from samples.
excetra! oops.. excellent!!
Glad you enjoyed our video! We have a ton more videos like this on our channel. We hope you will join our community!
wow.....
Thanks! Check out the playlist ruclips.net/video/ukzFI9rgwfU/видео.html to dive in deeper! :)
You are awesome nigga , I watched about 15-20 videos for better explanation of unsupervised, lately found you.. the way you expound it just got fit into my thick skull... thanks mann... you tooo good apeksha ...
Hi Vinay, we appreciate your kind comment. We will definitely send your regards to Apeksha. Do show your love and support by subscribing to our channel and also giving a thumbs up to our videos. Cheers!