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Hi 👋, I'm João Pedro Lavor

A passionate data scientist working at Blueshift Brasil.

jplavorr

jplavorr

Connect with me:

https://www.linkedin.com/in/joão-pedro-lavor-65162312b/ @jplavorr

Languages and Tools:

aws azure docker flask gcp git hive linux matlab mongodb mssql mysql opencv pandas postgresql postman python pytorch scikit_learn seaborn sqlite tensorflow

jplavorr

 jplavorr

jplavorr

João Pedro Lavor's Projects

amostragem icon amostragem

Para os trabalhos do mestrado na área de amostragem

aws-data-wrangler icon aws-data-wrangler

Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

big-data-with-pyspark icon big-data-with-pyspark

Advance your data skills by mastering Apache Spark. Using the Spark Python API, PySpark, you will leverage parallel computation with large datasets, and get ready for high-performance machine learning. From cleaning data to creating features and implementing machine learning models, you'll execute end-to-end workflows with Spark. The track ends with building a recommendation engine using the popular MovieLens dataset and the Million Songs dataset.

computervision icon computervision

Welcome to my Computer Vision Projects repository! This is a comprehensive collection of various projects that I've undertaken in the field of computer vision, exploring a range of technologies, tools, and techniques.

data-scientist-with-python icon data-scientist-with-python

In this track, you'll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you'll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You'll then work with real-world datasets to learn the statistical and machine learning techniques you need to train decision trees and use natural language processing (NLP). Start this track, grow your Python skills, and begin your journey to becoming a confident data scientist.

etl_pentaho icon etl_pentaho

Desenvolvimento de um Data Warehouse utilizando a ferramenta Pentaho Data Integration

fashion-mnist icon fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

finance-with-python icon finance-with-python

Analyze the financial market and set up strategies to improve investments with Data Science & Machine Learning

jplavorr.github.io icon jplavorr.github.io

This platform is dedicated to showcasing my projects in the fields of Machine Learning and Data Science. Browse through my portfolio to discover a variety of projects, from exploratory data analysis to predictive modeling. Stay tuned for regular updates and new additions to my collection.

kedro_tutorial icon kedro_tutorial

Starting my studies with the kedro framework for orchestrating machine learning pipelines.

m-todo-de-suaviza-o-direta icon m-todo-de-suaviza-o-direta

Nesse trabalho se encontra o trabalho realizado para cadeira de séries temporais sobre o método da suavização direta.

marketing-analytics icon marketing-analytics

Gain the Python skills you need to make better data-driven marketing decisions. In this track, you’ll learn how to analyze campaign performance, measure customer engagement, and predict customer churn. Working with real-world data, including retail transactions, you'll discover how to analyze social media data, extract insights from text data, and gain market basket analysis skills that will help you better understand your customers. You’ll also use statistical models and machine learning to forecast customer lifetime value. Through hands-on activities, you’ll use popular packages such as pandas, Matplotlib, tweepy, NLTK, seaborn, NumPy, SciPy, and scikit-learn to help you improve your company’s marketing strategy. By the end of the track, you'll be ready to navigate the world of marketing using Python.

math-behind-moneyball-with-python icon math-behind-moneyball-with-python

In this repository I will start a series, based on Coursera's 'Math Behind Moneyball' course (which is about Data Science in sports). I will reproduce the content seen in the course using Python and drawing conclusions from the data.

math-projects icon math-projects

As my background is in mathematics, I have a huge interest in applications of programming in the field. Here are some projects where I solve math problems with programming techniques.

microsoft-data_scientist. icon microsoft-data_scientist.

Learn new skills and discover the power of Microsoft products with step-by-step guidance. Start my journey by exploring the learning paths and modules to prepare for microsoft certification exam.

mlops icon mlops

This project is an open-source initiative that aims to provide a hands-on learning experience for anyone interested in the emerging field of Machine Learning Operations, or MLOps.

mlopsproject icon mlopsproject

Project for mlops end to end project with CI/CD pipelines

recommendation-systems- icon recommendation-systems-

Here you can find all my study on recommender systems, which I used to build a recommendation model in a work with big data applied in spark and tensorflow.

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