Hi everyone,

I am a little bit obsessed with data engineering and lately I have been working on several open source projects about this topic, here is a list of repositories and technologies used in each one, if you decide to go deeper into this funny world then these repositories could help you as a guide.

❤ means "I like this one"

❤ Tracking your Uber Rides and Uber Eats expenses through a data engineering process

Technologies and skills:

Python, Docker, Apache Airflow, AWS Redshift, Power BI, data modelling, Task schedulling, ETL and ELT processes, Data warehousing, Cloud

❤ Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag

Technologies and skills:

Python, Docker, Big Data, Cloud, BigQuery, Workflow Engines, GCP, Task scheduler, Google Cloud Platform, Dataproc cluster, GCS, Google Cloud Storage, Redis, DAG, Parallel Processing, Apache Spark

❤ Building Big Data Pipelines in the Cloud with AWS EMR

Technologies and skills:

Python, PySpark, AWS EMR, Task Schedulling, IAC, EC2 Instances, Apache Spark, Cloud

❤ Building a Lossless Data Compression and Data Decompression Pipeline

Technologies and skills:

Python, Data compression, BZIP2, Parallel programming

Learn how to dockerize an Apache Spark Standalone Cluster

Technologies and skills:

Python, Jupyter Notebook, Apache Spark, Docker, docker-compose, Hive

❤ Dockerizing and Consuming an Apache Livy environment

Technologies and skills:

Python, Big Data, Docker, docker-compose, Apache Livy, Apache Spark, PostgreSQL, PySpark, Jupyter Notebook

❤ Design, Development and Deployment of a simple Data Pipeline

Technologies and skills:

Python, data Modelling, Docker, docker-compose, PostgreSQL, data pipeline, FastApi

Dockerizing a Python Script for Faster Web Scraping

Technologies and skills:

Python, Docker, Sqlite, Dockerfile, Web scraping, Data pipeline, FastApi

Understanding Similarity Measures for Text Analysis

Technologies and skills:

Python, Machine Learning, Similarity measures, Distance metrics, Text Analysis

❤ Learn how to build a content-based Movie Recommender System

Technologies and skills:

Python, Machine Learning, TF-IDF, Cosine similarity, BM25, BERT, NLP, word2vec, Text Analysis, recsys

A Text Analysis of Speeches

Technologies and skills:

Python, Machine Learning, NLP, word2vec, Text Analysis, Sentiment Analysis, PCA, t-SNE, Word Embeddings, Text Preprocessing, Web scraping, Data Visualization, Mexico

❤ Dropout Students Prediction

Technologies and skills:

R, Genetic algorithm, Neural Networks, K-Means, Clustering, Machine Learning

I will be working on more complex projects in the next months using modern tech data stacks.