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Customer segmentation model based on credit cards behavior
Building a customer segmentation based on credit card payments behavior during the last six months to define marketing strategies.
A Data Engineer And Machine Learning Engineer
Data engineer with experience in projects focused on helping companies to maximize their potential through the integration of multiple data sources. In this way, they can make intelligent decisions based on these to obtain greater performance and profitability supported by the latest technological advances.
Skills in designing, developing, and implementing data architectures in cloud environments involving ETL processes for Big Data projects applying distributed computing, automation in data pipelines, deployment of predictive models of Machine Learning, and Deep Learning in order to extract insights reflected in dashboard for the different stakeholders of the projects. Finally, I am passionate about sharing and communicating valuable ideas that impact and help others to learn through them.
Aug 2018 - Mar 2019
IBM on Coursera
Aug 2019
International University Foundation of La Rioja - UNIR
Jan 2020
Holberton School
DeepLearning.AI TensorFlow Developer
Deep Learning Specialization
MicroMaster Statistics and Data Science, MITx on edX
Mathematics for Machine Learning Specialization
Machine Learning Engineer Nanodegree on Udacity
Programming language: Python, Scala, Spark, SQL
Visualization: Tableau, Power BI, Seaborn, Streamlit
Library: scikit-learn, TensorFlow, PyTorch
Statistical modeling
Supervised learning: Decision Tree, Regression, Bayesian, Emsemble, XGBoost
Unsupervised learning: Clustering
Deep Learning: CNN, ANN, RNN
AWS: EC2, SageMaker, Comprehend, S3, QuickSight, Api Gateway, Lambda, EMR, Glue, RDS, Stepfunctions
GCP: Cloud Storage, BigQuery, Compute Engine, Cloud Functions
Passionate about the business
Curious about data and research
Critical thinking
Strategic, proactive and cooperative
Building a customer segmentation based on credit card payments behavior during the last six months to define marketing strategies.
Forecast forecast the energy consumption of 369 customers based on historical data from January to April 2014 using 3 algorithms with the AWS cloud service.
Forecast through time series the number of searches for the year 2021 of the main financial products based on weekly historical data of 5 years.
The main objective of this article is to share the main findings about sentiment analysis in the banking sector using the Twitter API, AWS Comprehend and AWS SageMaker.
According to economic projections regarding Peruvian restaurants in Colombia, they are expected to exceed sales of 62 million dollars by 2019.
El objetivo es leer un archivo en formato AVRO alojado en un bucket de S3, ejecutar el job y finalmente guardar los resultados en una ruta específica de S3.
you are watching videos on Facebook about how to cook, specifically how to make cakes, pastries, and lasagna. At the end of a video, you will be able to see videos similar to the ones you have already seen, and how you like to watch cooking videos you keep clicking on.
The main objective of this article is to try to understand what happens behind our shell when we type ls -l.
The Standard C Library, also known as the ISO C Library, is a collection of macros, types and functions for tasks such as input/output processing, string handling.
The creation of an executable C module from a source code is basically a three-stage process
Linux is a fairly flexible operating system that can be reflected in the creation of the links. But what are links?
There are many commands for the Linux operating system, however, we will explain on this occasion how important it is to know how to use the “ls” command.
I'm always looking for a new problem to solve, so if you have any problem that you need help with or think we can work together, don't hesitate to contact me
cj.barros07@gmail.com
Barranquilla, Colombia