Fecha: 3 de febrero de 2026
Vehículo: VW Beetle II (5C) Fase 2 "Dune" BlueMotion · 1.4 TSI 150CV (CZDA) · Año 2016 · 47.000 km · Siniestro total
Ubicación: Barcelona 08015 (Eixample Esquerra / Avda Roma)
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| ❯ stack install shakespeare 2&> /tmp/aux.txt | |
| sydtest.cabal is up-to-date | |
| sydtest-aeson.cabal is up-to-date | |
| sydtest-amqp.cabal is up-to-date | |
| sydtest-autodocodec.cabal is up-to-date |
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| #!/bin/bash | |
| for branch in `git branch -r | grep -v HEAD`;do echo -e `git show --format="%ci\t%cr\t%cN" $branch | head -n 1` \\t$branch; done | sort -r |
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| for var in MY_ENV_VAR_1 MY_ENV_VAR_2; do | |
| if [[ -z "${!var:-}" ]]; | |
| then | |
| echo "You need to provide a value for env variable $var" | |
| exit 1 | |
| fi | |
| done |
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| CREATE INDEX ON :Block(height); | |
| CREATE INDEX ON :Transaction(hash); | |
| CREATE INDEX ON :Output(tx_hash, output_index); | |
| CREATE INDEX ON :Address(address_string); | |
| LOAD CSV WITH HEADERS FROM "http://storage.googleapis.com/bitcoin-neo4j-etl/blocks.csv" AS row | |
| MERGE (b:Block {height: toInt(row.number)}) | |
| ON CREATE SET | |
| b.hash = row.hash, | |
| b.size = toInt(row.size), |
I hereby claim:
- I am tonicebrian on github.
- I am tonicebrian (https://keybase.io/tonicebrian) on keybase.
- I have a public key ASCRxHtGVkzN4Jafqr5R2uv0u5SniW01xVznq_VF-kidkgo
To claim this, I am signing this object:
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| # Create a SSH connection | |
| import paramiko | |
| import os | |
| ssh = paramiko.SSHClient() | |
| ssh._policy = paramiko.WarningPolicy() | |
| ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) | |
| ssh_config = paramiko.SSHConfig() | |
| user_config_file = os.path.expanduser("~/.ssh/config") |
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| # ============= | |
| # Introduction | |
| # ============= | |
| # I've been doing some data mining lately and specially looking into `Gradient | |
| # Boosting Trees <http://en.wikipedia.org/wiki/Gradient_boosting>`_ since it is | |
| # claimed that this is one of the techniques with best performance out of the | |
| # box. In order to have a better understanding of the technique I've reproduced | |
| # the example of section *10.14.1 California Housing* in the book `The Elements of Statistical Learning <http://www-stat.stanford.edu/~tibs/ElemStatLearn/>`_. | |
| # Each point of this dataset represents the house value of a property with some | |
| # attributes of that house. You can get the data and the description of those |