#general
Company-wide announcements and work-based matters
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Nityesh Agarwal
September 15, 2020 at 08:30 PM
Nityesh Agarwal
July 31, 2020 at 07:59 PM
Nityesh Agarwal
July 15, 2020 at 06:51 PM
Paridhi Agarwal
July 12, 2020 at 07:57 PM
Nityesh Agarwal
July 01, 2020 at 07:19 PM
Paridhi Agarwal
July 01, 2020 at 06:15 PM
Nityesh Agarwal
June 30, 2020 at 12:19 PM
Nityesh Agarwal
June 17, 2020 at 07:02 PM
Best Git tutorial ever!
Nityesh Agarwal
April 19, 2020 at 07:19 PM
Nityesh Agarwal
April 19, 2020 at 06:41 PM
Nityesh Agarwal
April 19, 2020 at 05:52 PM
Nityesh Agarwal
April 18, 2020 at 07:29 PM
"Create new relevant articles" hai hi nahiii!!!!
Paridhi Agarwal
April 16, 2020 at 08:30 AM
scores = {leaf_size: get_mae(leaf_size, train_X, val_X, train_y, val_y) for leaf_size in candidate_max_leaf_nodes}
best_tree_size = min(scores, key=scores.get)
Paridhi Agarwal
April 15, 2020 at 03:09 PM
import sys
candidate_max_leaf_nodes = [5, 25, 50, 100, 250, 500]
Write loop to find the ideal tree size from candidate_max_leaf_nodes
min_val = sys.maxsize
for max_leaf_nodes in candidate_max_leaf_nodes:
my_mae = get_mae(max_leaf_nodes, train_X, val_X, train_y, val_y)
if my_mae<min_val:
min_val = my_mae
tree_size = max_leaf_nodes
Store the best value of max_leaf_nodes (it will be either 5, 25, 50, 100, 250 or 500)
best_tree_size = max_leaf_nodes
print(best_tree_size)
Check your answer
step_1.check()
Paridhi Agarwal
April 13, 2020 at 08:27 PM
Nityesh Agarwal
April 13, 2020 at 08:11 PM
Paridhi Agarwal
April 13, 2020 at 08:05 PM
Nityesh Agarwal
April 12, 2020 at 07:29 PM
Nityesh Agarwal
April 12, 2020 at 07:25 PM
Paridhi Agarwal
April 10, 2020 at 07:30 PM
Nityesh Agarwal
April 08, 2020 at 08:03 PM
Paridhi Agarwal
April 05, 2020 at 08:42 PM
recent_grads['Sample_size'].hist(bins=25, range=(0,5000))
Nityesh Agarwal
April 05, 2020 at 07:56 PM
Nityesh Agarwal
April 05, 2020 at 11:14 AM
Nityesh Agarwal
April 05, 2020 at 11:13 AM
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