Actions might effect not only the current reward, but also the next scenario and, via that, all subsequent rewards, in the most intriguing and complex circumstances. The two most essential distinguishing elements of reinforcement learning are trial-and-error searching and delayed rewards.
Reinforcement can be used to teach new abilities, replace an interfering behaviour with a replacement behaviour, promote suitable behaviours, or increase on-task behaviour (AFIRM Team, 2015). Reinforcement may appear to be a straightforward method that many teachers employ, but it is frequently underutilised.
Learner's Ratings
4.4
Overall Rating
71%
10%
10%
5%
4%
Reviews
S
Shafi Akhtar
5
None
A
Aniket Kumar prasad
5
Very helpful and easy to understand all the concepts, best teacher for learning ML.
R
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)
M
Mohd Mushraf
5
Amazing Teaching
J
Juboraj Juboraj
5
Easy to understand & explain details.
J
Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
S
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
N
Neel Khairnar
5
Kushal is very good explainer he is covering all topics nicely 👍
Share a personalized message with your friends.