Data Engineering ZoomCamp

Overview

Data Engineering ZoomCamp

I'm partaking in a Data Engineering Bootcamp / Zoomcamp and will be tracking my progress here. I can't promise these notes will be neat and tidy, but I hope they can help anyone who is working through this bootcamp.

I'll aim to document any problems or errors I come across during my journey, and describe concepts that I found tricky.

Each week I'll work through a series of videos and follow this up with homework exercises.

The Task

The goal is to develop a data pipeline following the architecture below. We will be looking at New York City Taxi data!

Tools

We'll use a range of tools:

Progress

  • Week1

    PostgreSQL | Terraform | Docker | Google Cloud Platform

    This week was a lot of setup, and a lot of work! Here I was introduced to Docker - a framework for managing containers. I created some containers for PostgreSQL and PgAdmin, before finally creating my own image, which when run, created and populated tables within my PostgreSQL database.

    Next up I learned a bit about Google Cloud Platform (GCP), which is suite of Google Cloud Computing resources. Here I setup a service account (more or less a user account for service running in GCP and even setup a Virtual Machine, and connected to it using SSH right from my terminal.

    I was also introduced to Terraform - an infrastructure-as-code tool. I used this to generate some stuff on GCP - Big Query and Google Cloud Storage - from a simple script.

    I enjoyed this week, although it was heavy going. A lot of late nights trying to understand new concepts and fix unexpected bugs. Although I'm by no means an expert in any of these tools, I do feel more confident in understanding and utilsing them.

  • Week 2

    This week I'm learning about Airflow!

  • Week 3: Pending...

  • Week 4: Pending...

  • Week 5: Pending...

  • Week 6: Pending...

Owner
Aaron
I am a neuroscience graduate currently working in engineering systems and self-studying data engineering.
Aaron
Auto HMM: Automatic Discrete and Continous HMM including Model selection

Auto HMM: Automatic Discrete and Continous HMM including Model selection

Chess_champion 29 Dec 07, 2022
Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit

7 Oct 13, 2022
Direct LiDAR Odometry: Fast Localization with Dense Point Clouds

Direct LiDAR Odometry: Fast Localization with Dense Point Clouds DLO is a lightweight and computationally-efficient frontend LiDAR odometry solution w

VECTR at UCLA 369 Dec 30, 2022
Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals

LapDepth-release This repository is a Pytorch implementation of the paper "Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals" M

Minsoo Song 205 Dec 30, 2022
A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for ONNX.

sam4onnx A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for

Katsuya Hyodo 6 May 15, 2022
Hands-On Machine Learning for Algorithmic Trading, published by Packt

Hands-On Machine Learning for Algorithmic Trading Hands-On Machine Learning for Algorithmic Trading, published by Packt This is the code repository fo

Packt 981 Dec 29, 2022
Python based framework for Automatic AI for Regression and Classification over numerical data.

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

BlobCity, Inc 141 Dec 21, 2022
A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python.

c is for Camera A 35mm camera, based on the Canonet G-III QL17 rangefinder, simulated in Python. The purpose of this project is to explore and underst

Daniele Procida 146 Sep 26, 2022
Concept drift monitoring for HA model servers.

{Fast, Correct, Simple} - pick three Easily compare training and production ML data & model distributions Goals Boxkite is an instrumentation library

98 Dec 15, 2022
Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Ali Aliev 15.3k Jan 05, 2023
Jupyter notebooks showing best practices for using cx_Oracle, the Python DB API for Oracle Database

Python cx_Oracle Notebooks, 2022 The repository contains Jupyter notebooks showing best practices for using cx_Oracle, the Python DB API for Oracle Da

Christopher Jones 13 Dec 15, 2022
SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks

SalFBNet This repository includes Pytorch implementation for the following paper: SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolu

12 Aug 12, 2022
Source code for our paper "Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures"

Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures Code for the Multiplex Molecular Graph Neural Network (M

shzhang 59 Dec 10, 2022
Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem

Benchmarking nearest neighbors Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem, but so far t

Erik Bernhardsson 3.2k Jan 03, 2023
Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization

Towards Ultra-Resolution Neural Style Transfer via Thumbnail Instance Normalization Official PyTorch implementation for our URST (Ultra-Resolution Sty

czczup 148 Dec 27, 2022
CVPR2020 Counterfactual Samples Synthesizing for Robust VQA

CVPR2020 Counterfactual Samples Synthesizing for Robust VQA This repo contains code for our paper "Counterfactual Samples Synthesizing for Robust Visu

72 Dec 22, 2022
Pyramid Pooling Transformer for Scene Understanding

Pyramid Pooling Transformer for Scene Understanding Requirements: torch 1.6+ torchvision 0.7.0 timm==0.3.2 Validated on torch 1.6.0, torchvision 0.7.0

Yu-Huan Wu 119 Dec 29, 2022
GluonMM is a library of transformer models for computer vision and multi-modality research

GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon

42 Dec 02, 2022
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

Benedek Rozemberczki 697 Dec 27, 2022
Code for CPM-2 Pre-Train

CPM-2 Pre-Train Pre-train CPM-2 此分支为110亿非 MoE 模型的预训练代码,MoE 模型的预训练代码请切换到 moe 分支 CPM-2技术报告请参考link。 0 模型下载 请在智源资源下载页面进行申请,文件介绍如下: 文件名 描述 参数大小 100000.tar

Tsinghua AI 136 Dec 28, 2022