My Core Project - DataSource.ai

Data science competitions for startups and SMB's

DataSource.ai democratize data science competitions, allowing startups and SMBs to sponsor challenges and award prizes accessible to them. We give startups access to a global talent pool to help them solve their problems using machine learning.

A side hustle - Datacademy.dev

Learning data science solving challenges

In datacademy.dev our users solve challenges in python, statistics, mathematics, visualizations, ML, DL and others. Once they solve the challenge, they upload it to the platform, and review the code with the community.

Helping others - Datajobs.dev

Helping data scientist get a job in data

Users receive a weekly data science job listing with curated and selected job opportunities, where they can work as a Data Scientist, ML Engineer or Data Engineer with great job benefits and a completely remote work culture.

Teaching what I know - MakeitReal.camp

I love to teach and mentor others

In the evenings I teach everything I've learned as a data scientist, helping my friends at MakeitReal to train their students and make them competitive in this discipline. It is an online and live intensive bootcamp of 142 hours.

My Publication - NarrativeText.co

I share openly some of my notebooks

I share my notebooks on a site called NarrativeText.co, where I can publish them as articles and reach a wider audience in a data scientist friendly format. Notebooks are my favorite space for analysis.

Access to my ML APIs - Dataendpoint.co

Creating Machine Learning APIs

I've been creating a series of machine learning models that I share via APIs hosted on a machine learning API marketplace called dataenpoint.co. Users just follow the instructions to make requests to these APIs.

Domain Expertise

The 3 Basic Principles of a Data-Driven Company

The data is sometimes called the “new oil” a newly discovered source of wealth that is extracted from the depths of corporate and government archives. Some accountants are so excited about the potential value of the data that they count it in the ...

API

Customer Conversion Prediction

In this endpoint we are making predictions of customer conversion, using decision trees, where the selected characteristics are:age (numeric)balance: (numeric) account balancecampaign: number of contacts performed during this campaign and for this...

Writting

Interview To The Winners Of The Data Science Competition "Predicting App Ratings In Google Play Store"

As usual, we have given ourselves the task of interviewing the winners of the competition "Google Play Store Rating Prediction" that ended a few days ago, having as winner Edimer "Siderus" from Colombia and with a score of 0.698709403908066 and wh...

Domain Expertise

How to Make Your Company a Data-Driven Organization

Startups, SMBs or company founders, managers or decision makers often claim that they are “data rich but information poor”. This statement is in many cases only partially correct because it hides a misconception about the data life cycle. The fact...

Domain Expertise

Why Data Science Competitions Are Important for Startups and SMBs

Today, large companies have large I+D budgets that allow them to experiment and be at the cutting edge of new technologies; always adopting the newest, trying to adapt it to their own needs, trying to find the hidden value in each of them.

Writing

Understanding Python's Collections Module

The Python collections module has different specialized data types that function as containers and can be used to replace the general purpose Python containers (`dict`, `tuple`, `list` and `set`). We will study the following parts of this module:

Writing

Identifying Linear Relationships Between Variables In Machine Learning

Linear models assume that the independent variables, X, take on a linear relationship with the dependent variable, Y. This relationship can be dictated by the following equation (Equation of a Straight Line)

Writing

Using Python And Pandas Datareader to Analyze Financial Data

Finance and economics are becoming more and more interesting for all kinds of people, regardless of their career or profession. This is because we are all affected by economic data, or at least we are increasingly interested in being up-to-date, a...

Writing

21 Resources for Learning Math for Data Science

Let’s be honest, most people didn’t do very well in math in school, maybe not even in college, and this is very scary and creates a barrier for those who want to explore this discipline called data science.A few days ago I published a post in Towa...

Writing

Study Plan for Learning Data Science Over the Next 12 Months

We are ending 2020 and it is time to make plans for next year, and one of the most important plans and questions we must ask is what do we want to study?, what do we want to enhance?, what changes do we want to make?, and what is the direction we ...

Notebook

Building a Product Recommendation System with Collaborative Filtering

We will go deeper into building a product recommendation system that we can better target customers with, using product recommendations that are tailored to individual customers. Studies have shown that customized product recommendations improve c...

Writing

Using Predictive Power Score to Pinpoint Non-linear Correlations

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense, correlation is any statistical association, although it commonly refers to the ...

Writing

How to Use Python Datetimes Correctly

The datetime module provides classes to manipulate dates and times in a simple and complex way. While date and time arithmetic is supported, the application focuses on the efficient extraction of attributes for formatting and manipulating output

Notebook

Using Pandas Profiling to Accelerate Our Exploratory Analysis

Pandas Profiling is a library that generates reports from a pandas DataFrame. The pandas df.describe() function that we normally use in Pandas is great but it is a bit basic for a more serious and detailed exploratory data analysis. pandas_profili...

Writing

Creating the Whole Machine Learning Pipeline with PyCaret

This tutorial covers the entire ML process, from data ingestion, pre-processing, model training, hyper-parameter fitting, predicting and storing the model for later use.We will complete all these steps in less than 10 commands that are naturally c...