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{
  "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json",
  "basics": {
    "name": "Bernardo Galvão",
    "label": "ML Engineer",
    "image": "https://avatars.githubusercontent.com/u/17158288?v=4",
    "email": "[email protected]",
    "url": "https://bernardo-galvao.dev",
    "summary": "Jack-of-all-trades Data Scientist turned MLOps Engineer. My combined experience in Data Science and Software Engineering is resulting in the perfect positioning for this new area of expertise. Currently acquiring DevOps skills and counting. Hire me if you need someone to operationalize the Machine Learning.\n",
    "location": {

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Host github.com
	User git
	Port 443
	Hostname ssh.github.com
	IdentityFile ~/.ssh/github
	TCPKeepAlive yes
	IdentitiesOnly yes

bgalvao

Train Test Validation Suite

The suite is composed of various checks such as: Train Test Label Drift, Train Test Feature Drift, Date Train Test Leakage Overlap, etc...
Each check may contain conditions (which will result in pass / fail / warning / error

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# codeinterview.io

# You are envolved in a development of a new binary serialization 
# protocol. Your first task is to implemnt `enumerateChars` 
#  function. The function builds dictionary where key is character found in 
#  the strings and value corresponding coordinates of that character (string index 
#  in the sequence, character index in the string)
#  
#  Arguments:
# strings: list of strings

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{
  "basics": {
    "name": "Bernardo Galvão",
    "label": "MLOps Engineer",
    "image": "https://avatars.githubusercontent.com/u/17158288?v=4",
    "email": "[email protected]",
    "phone": "",
    "url": "dev.brnrdo.live",
    "summary": "Data Scientist turning into a full-fledged MLOps Engineer. My experience in Data Science and Software Engineering is resulting in the perfect positioning for this new area of expertise. Currently acquiring DevOps skills and counting. Hire me if you need someone to operationalize the Machine Learning Operations in your company and let the Data Scientists focus on their modelling task: I'll handle the operations.",
    "profiles": [

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Prereqs: install jsonnet, yaml2jsonnet (optional) and yq:

If you already have .yaml files lying around, or prefer to start with them, you don't have to start from scratch: convert them to jsonnet using yaml2jsonnet

yaml2jsonnet ../config/authelia/configuration.yaml | jsonnetfmt - -o config.authelia.jsonnet

Let that be your starting point. Now edit to your will. If you want to test it (see what it renders) or save it, then:

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MLFLOW_DB_NAME=mlflow_db
MLFLOW_DB_PASSWORD=use_vault
MLFLOW_DB_CONNECTION_URI=postgresql+asyncpg://postgres:${MLFLOW_DB_PASSWORD}@mlflow-db:5432/${MLFLOW_DB_NAME}

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{
    "workbench.colorTheme": "Mayukai Mirage Gruvbox Darktooth",
    "gitlens.hovers.currentLine.over": "line",
    "gitlens.codeLens.enabled": false,
    "files.associations": {
        "*.nomad": "terraform",
        "*.hcl": "terraform"
    },
    "editor.fontFamily": "'Iosevka', 'monospace', monospace, 'Droid Sans Fallback'",
    "editor.fontWeight": "bold",

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(base) [user@machinelmao openmlops]$ minikube start --kubernetes-version=v1.17.17
😄  minikube v1.23.2 on Arch 21.1.6
✨  Using the docker driver based on user configuration
👍  Starting control plane node minikube in cluster minikube
🚜  Pulling base image ...
🔥  Creating docker container (CPUs=2, Memory=3900MB) ...
🐳  Preparing Kubernetes v1.17.17 on Docker 20.10.8 ...
    ▪ Generating certificates and keys ...
    ▪ Booting up control plane ...
💢  initialization failed, will try again: wait: /bin/bash -c "sudo env PATH=/var/lib/minikube/binaries/v1.17.17:$PATH kubeadm init --config /var/tmp/minikube/kubeadm.yaml  --ignore-preflight-errors=DirAvailable--etc-kubernetes-manifests,DirAvailable--var-lib-minikube,DirAvailable--var-lib-minikube-etcd,FileAvailable--etc-kubernetes-manifests-kube-scheduler.yaml,FileAvailable--etc-kubernetes-manifests-kube-apiserver.yaml,FileAvailable--etc-kubernetes-manifests-kube-controller-manager.yaml,FileAvailable--etc-kubernetes-manifests-etcd.yaml,Port-10250,Swap,SystemVerificatio

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#!/usr/bin/env python3

import os
from shutil import copyfile

home_dir = os.getenv('HOME')  # only works on Linux
desktop_dir = os.path.join(home_dir, 'Desktop')
chrome_based_browsers = ['brave', 'chrome', 'chromium', 'vivaldi']