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glue-etl-pyspark

AWS Glue ETL job in pyspark

glueetl

A command line tool to help deploy AWS Glue Jobs at ease :)

gluejobutils

Python 2.7 utility functions to include with AWS glue jobs

gluesparkproject

Project using Aws glue with sparksql jobs, Athena , Aws lambda and Quicksight

google-airflow-premier-league

Data Warehousing Made Easy with Google BigQuery and Apache Airflow

google_cloud_function

googlebigqueryawsairflowexample

AWS Managed Apache Airflow Machine Learning workflow example

grind-75

Leetcode Solutions in Python for Grind 75

grind169

An effort to solve the list of problems at https://www.techinterviewhandbook.org/grind75

grokking-the-object-oriented-design-interview

handle-api-with-airflow-example

Handle Api Response with Airflow Example. Read the article for a more detailed walk-through of the repository.

helper_functions

horse_racing_etl_redshift_spark

Pipeline stages CSV and JSON files from S3 into Redshift, transforms with PySpark, and loads denormalised analytics tables in Redshift.

hotel_booking_cancellation_prediction

Hotel Booking Cancellation Prediction: A machine learning model that predicts the likelihood of hotel booking cancellations, deployed as a real-time web service using FastAPI and Docker. Enhance your hotel's operational efficiency, revenue optimization, and customer experience with data-driven decisions.

house-prediction

Testing MLOps approach to predict houses' prices in Saint-Petersburg

house-price-prediction-to-deployment

king County housing price prediction model creation to deployment using Flask.

houseskagglechallenge

housing-project

Housing data pipeline

how-to-do-tests-in-python

httpcli

A Proof of concept of a modern python CLI with click, pydantic, rich and anyio

inefficientcode

a respository for code used on the inefficient_code() blog

instacart-market-basket-analysis

Instacart, a grocery ordering and delivery app, aims to make it easy to fill your refrigerator and pantry with your personal favorites and staples when you need them. After selecting products through the Instacart app, personal shoppers review your order and do the in-store shopping and delivery for you. Instacart’s data science team plays a big part in providing this delightful shopping experience. Currently they use transactional data to develop models that predict which products a user will buy again, try for the first time, or add to their cart next during a session.We need to use this anonymized data on customer orders over time to predict which previously purchased products will be in a user’s next order.

interactive-coding-challenges

120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

ipl-data-analysis

Data Analysis and Visualizations done on IPL dataset

irish_weather_data_viz

A tutorial about data handling using SQL

java-email_sender

An email sending application using java, java-mail jar

joao_siqueira_portifolio

My Repository of Data Science Projects

job-data-pipeline

My data engineering project

jupyterhub-on-kubernetes

Jupyterhub deployment with Kubernetes (K8s) on Google Kubernetes Engine (GKE). This project is part of DigiKlausur project to deploy jupyterhub on Kubernetes (Google Kubernetes Engine) for teaching.

kafka-pipeline

Create a streaming pipeline using Kafka and Kafka Connect