What Are the Expected Results of a Data Science Project?
From a company perspective, data science projects should always be viewed as experiments. Remember that we are talking about science, and science bases many of its theories on the results of a series of experiments. From here, many companies start...
Why Decorators In Python Are Pure Genius?
Analyze, test, and re-use your code with little more than an @ symbolIf there’s one thing that makes Python incredibly successful, that would be its readability. Everything else hinges on that: if code is unreadable, it’s hard to maintain. It’s al...
¿What Is A Data Science Tournament?
Data science, as opposed to web or mobile development, has a relatively easy way to measure the outcome: through evaluation metrics. In software development the outcome expected by stakeholders is given by a number of subjective things, such as us...
How Poker Can Teach Data Science Fundamentals
Connections made between data science and gaming tend to have to do with AI, and how it is tested and developed through certain games. Case in point, some of the resources for learning math for data science that have been discussed here in the pas...
How the Biggest Companies in the World Design Machine Learning Applications
I'm often asked, "what kind of machine learning project should I work on?"And I usually answer with "follow your curiosity."Why?Because of how experimental machine learning is, it's in your best interest to figure things out through tinkering. By ...
Top 10 Data Science Leaders You Should Follow
Having great mentors to learn from has been a huge blessing throughout my data science career, or even in life.I still remember the defining moment when I decided to transition from physics into data science during my final year in university.The ...
Customize your Jupyter Notebooks
IntroductionJupyter Notebook is a great programming environment and often the most popular choice for data scientists or data analysts that are coding in python. Unfortunately, its default settings do not allow the level of customization that you ...
What's new in DataSource.ai?
Hello everyone, I'm Daniel Morales co-founder of DataSource.ai and today I want to share with you very good news and the new advances we are making in order to have an excellent data scientist community globally. New CEOThis is perhaps the most im...
Interview With The Winners of the Data Science Competition "Predicting Purchase Intention on a Web Page"
Learn how they made their machine learning models and what tools they used with this interview to the Top 5 of the leaderboard of the competition. A few days ago we finished the data science competition called "Predicting Purchase Intention on a W...
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...
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...
What Is Open Innovation In Data Science?
Open innovation is a term used to promote a different and open mindset towards innovation that goes against the secrecy and traditional mentality of corporate R&D labs. The use of the term "open innovation" refers to the growing acceptance of ...
How to Use Python Datetimes Correctly?
Datetime is basically a python object that represents a point in time, like years, days, seconds, milliseconds. This is very useful to create our programs.The datetime module provides classes to manipulate dates and times in a simple and complex w...
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...
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:-...
How to Make Your Company a Data-driven Organization?
Startup, SMB 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 t...
