Mohit Sinha mohit-sinha
mohit-sinha
/ yt_transcribe_n8n.json
Last active
December 16, 2025 14:08
YouTube Transcribe n8n workflow
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| { | |
| "name": "YouTube to PDF (via PDFShift)", | |
| "nodes": [ | |
| { | |
| "parameters": {}, | |
| "id": "d71f19df-2737-445f-aaa2-71284ddd9836", | |
| "name": "When clicking ‘Execute workflow’", | |
| "type": "n8n-nodes-base.manualTrigger", | |
| "typeVersion": 1, | |
| "position": [ |
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| from bayes_opt import BayesianOptimization | |
| from sklearn.cross_validation import KFold | |
| import xgboost as xgb | |
| import numpy | |
| def xgbCv(train, features, numRounds, eta, gamma, maxDepth, minChildWeight, subsample, colSample): | |
| # prepare xgb parameters | |
| params = { | |
| "objective": "binary:logistic", | |
| "booster" : "gbtree", |
mohit-sinha
/ lgb_bo.py
Created
June 27, 2018 11:51
Use this for LightGBM parameter optimisation by Bayesian optimisation.
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| import pandas as pd; | |
| import numpy as np; | |
| import lightgbm as lgb | |
| from bayes_opt import BayesianOptimization | |
| from sklearn.model_selection import cross_val_score | |
| def lgb_evaluate( | |
| numLeaves, | |
| maxDepth, | |
| scaleWeight, |