Simply described, a dataset in machine learning is a collection of data bits that may be considered as a single unit by a computer for analytic and prediction purposes. This means that the data gathered should be homogeneous and understandable to a machine that does not see data in the same manner that people do.
To teach machine learning algorithms how to execute various tasks, training datasets must be given into the algorithm first, followed by validation datasets (or testing datasets) to check that the model is correctly understanding the data.
To teach machine learning algorithms how to execute various tasks, training datasets must be given into the algorithm first, followed by validation datasets (or testing datasets) to check that the model is correctly understanding the data.
Machine Learning's Benefits:
Identifies trends and patterns quickly.
No need for human interaction (automation)
Ongoing Improvement
Managing data that is multi-dimensional and diverse.
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Muhammad Qasim
5
Hi Kushal ! Your way of teaching is extremely helpful and you are one of the best teacher in the world.
Extremely helpful and I recommend to my peer as well for this course.
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Shafi Akhtar
5
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Aniket Kumar prasad
5
Very helpful and easy to understand all the concepts, best teacher for learning ML.
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Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
V
VIKAS CHOUBEY
5
very nicely explained
V
Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
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Mohd Mushraf
5
Amazing Teaching
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Juboraj Juboraj
5
Easy to understand & explain details.
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Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
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Shaga Chandrakanth Goud
5
Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
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