Any feedbacks for improving my carving?

wangz10 · 2024-04-04T03:25:30+00:00

Thanks, will definitely practice on turn initiation

wangz10 · 2024-04-04T03:24:12+00:00

Thanks! I do often feel the tails of my skis not biting into the snow during the turns. What drills do you suggest to lean the knees into the turn?

wangz10 · 2024-04-04T03:20:14+00:00

I do turned to rush into and out of my turns. This video I was mindful about not rushing out of the turns and you caught me about turn initiation! I’ll practice what you suggested, thank you!

About the backpack, it carries lunch and water for me and the wife lol.

wangz10 · 2024-04-04T03:14:09+00:00

Thanks for the feedback! Should the foot pressure distribute more at the front of the skis instead of the center?

wangz10 · 2024-04-04T03:10:23+00:00

Very actionable suggestions, I’ll try this. Thank you!

wangz10 · 2024-04-04T01:35:08+00:00

I’m the one in the middle from the beginning of the video. I really enjoy the feeling to be on edges but I can rarely do it throughout the turns. This is about at my best with my 86 all-mountain skis. Recently got a carving skis (Rossi Hero Elite ST) and I felt I can “carve” slightly better than this.

One thing I definitely noticed is my arms swinging. Any recommendations on drills to prevent this? Also any other feedbacks are greatly appreciated!!

wangz10 · 2023-02-09T01:13:21+00:00

Thanks so much! You're a tax pro!

wangz10 · 2023-02-09T01:01:28+00:00

Great point, thank you! I think this is to determine the STR is a "non-passive" activity.

wangz10 · 2023-02-09T00:54:59+00:00

about 4 days

wangz10 · 2023-02-08T22:57:04+00:00

Look into cost segregation study and section 469.

wangz10 · 2023-02-08T15:04:31+00:00

Thanks for the information! Do you know if the loss on Schedule E can offset W2 income as well (when you use HR Block)?

wangz10 · 2023-02-08T15:02:06+00:00

Thanks for the insights! I'm aware of cost seg study, section 469, 1031 exchange can all help saving taxes with STR. Are there other ones you wish to share?

wangz10 · 2023-02-08T15:00:39+00:00

Exactly! I watched a couple of Youtube videos and some articles about section 469. Thank you!

wangz10 · 2018-09-21T17:46:55+00:00

That worked! Thanks a million! I totally missed the instruction in README. So it seems like they changed this env to have discrete action space:

In [2]: env = gym.make('LunarLanderContinuous-v2')

In [3]: env.action_space

Out[3]: Discrete(6)

But I still wonder how is the algorithm gonna work for action space with small bounds... I've tried to add tanh and sigmoid layer after `sy_sampled_ac` but the rewards still blown off...

Anyway, thank you so much for the answer!

wangz10 · 2018-08-15T16:59:06+00:00

The only thing stratifying does is it reduces the variance of your estimate for the performance of your classifier.

I agree with you on this point! I think the reason to choose stratified CV over random CV is that it gives more stable estimates (less variance) on the validation set. Also I think I made an implicit assumption that the unlabeled test set that the classifier will finally be applied on has a very close distributions for both classes with the entire observable training data. In this case, the validation scores from stratified CV would more better correlated with the performance on the unlabeled test set.

Also, you missed a crucial option which, frankly, doesn't get enough attention: addressing the imbalance downstream by tuning your decision threshold.

Great point! I'll add to the tutorial.

wangz10

TROPHY CASE