Reinforcement learning is a machine learning training strategy that rewards desirable behaviours while penalising undesirable ones. A reinforcement learning agent can perceive and comprehend its surroundings, act, and learn through trial and error in general.
Trajectory optimization, motion planning, dynamic pathing, controller optimization, and scenario-based learning policies for highways are some of the autonomous driving activities where reinforcement learning could be used. Learning automated parking policies, for example, can help with parking.
Learner's Ratings
4.4
Overall Rating
70%
11%
11%
5%
3%
Reviews
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.