About Me
I'm a very motivated and experienced data scientist that has worked in many different types of products and have owned some medals in data science competitions. So far, I've worked in 3 different consulting companies where I developed mor...
Also, I have many projects that I developed to data science competitions or to learn some specific techniques and so on. Only in open platforms like Github and Kaggle, I've worked in more than 50 data science projects;
I have many experiences in Data Visualization, Exploration, Machine Learning, Deep Learning, Timeseries, Computer Vision and lots of other tasks using data science techniques.
I'm a very active member of Kaggle (Google Company) that is the biggest knowledge crowdsourcing of data scientists in the world. It has more than 3 million registrations and almost 400k active members. It's known as the "house of data scientists" and I have the Tier of KERNELS GRANDMASTER there. I'm ranked on 13th over 108.5k+ other data scientists. Also, I have owned 15 gold medals, 8 silver medals and 18 bronze medals in my open project notebooks.
On this Google platform(Kaggle) my work has more than 3.8k of Votes, 3.7k of Forks and I have more than 2k of data scientists that follow me in my social media.
Please, visit many of my projects on Kaggle using the link: www.kaggle.com/kabure/kernels
If you need more informations, please let me know.
Show MoreSkills
Data & Analytics
Web Development
Software Engineering
Programming Language
Others
Development Tools
Database
Mobile Apps
Portfolio Projects

Company
IEEE-CIS Fraud Detection
Description
It was a very interset EDA and modeling to Detect Frauds.
It got more than 700 votes and have 680+ forks
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Python NumPy SciKit-LearnTools
Jupyter Notebook



Google Analytics Customer Revenue Prediction
https://www.kaggle.com/kabure/exploring-the-consumer-patterns-ml-pipelineCompany
Google Analytics Customer Revenue Prediction
Role
Data Scientist
Description
It was a project to understand customer patterns in google store.
I used all pydata stack to find very interesting and useful insights into the data. Also, I predicted the chance to the customer buy a product of google.
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Python SciKit-Learn Seaborn PandasMedia







