Building a data science team that works

Many companies are trying to build data science capabilities, for various reasons: either they saw that a competitor is extracting real value, or, more commonly, simple fear of missing out.  Sometimes these initiatives fail. Actually, rather often. But why is that and how to prevent it? In my experience, there are three key factors that … Read moreBuilding a data science team that works

Reinforcement Learning in Python, Part 1: Welcome to RL

Reinforcement Learning is a framework for tackling sequential decision problems: what to do next in order to maximize a reward (which might be delayed), on a changing universe (which might react to our actions). Examples of this include: Game playing: which actions are critical to win a game? Learning in a “small world”: what actions … Read moreReinforcement Learning in Python, Part 1: Welcome to RL

How to Scrape a job listing from StackOverflow 

In this guest post, Michael Heydt, the author of the Python Web Scraping Cookbook, shows how to scrape a job listing from StackOverflow using Python. It’s Easy to Scrape Stack Overflow StackOverflow actually makes it quite easy to scrape data from their pages. In this article, you’ll be shown how to use content from a posting … Read moreHow to Scrape a job listing from StackOverflow 

3 tricks for efficient data science

It’s amazing how little things can turn a data science / mathematical modelling project into a full-fledged mess.  There are easily avoidable traps, but unfortunately also easily forgotten: we love to pretend we “couldn’t do something that silly”. Following the principles below has saved me (and others) a lot of time and spared me from … Read more3 tricks for efficient data science

Multi-armed bandits, part 2

Implementation There are two important parts for the implementation: on one hand, we have to implement an environment that simulates the reward of the arms. The skeleton of this class is given below: class Arm(object): def __init__(self, params): ## passes the required parameters ## this could be the reward probability, or other parameter (mean, sigma) … Read moreMulti-armed bandits, part 2

4 reasons to invest in open-source data science training

With the ever-changing technology landscape come lots of challenges for companies. Specially around data science, where we are witnessing a constant expansion in technologies and tools. Every company is becoming increasingly data-driven, and the best way to remain relevant in the next five years is to be prepared. What concrete advantages does open-source data science … Read more4 reasons to invest in open-source data science training

Is it really worth learning AI/ML?

Every minute, a new data science course is born somewhere. Granted, I totally made this up but I might not be completely wrong. Lots of research groups are doing breakthroughs in data science and artificial intelligence everyday, and yes, there is hype, but there is also optimism, strongly supported by evidence.

So, is it really time to jump in and drop one’s career and everything to switch to AI? Is it finally time to join Coursera/Udacity/Edx/your favorite MOOC/university?

Well, no.

Read moreIs it really worth learning AI/ML?