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Human-Centric AI Manifesto: Or How To Try and DO No Harm
Recently I’ve said farewell to my academic career and switched back to industry. While I haven’t regretted that move for one moment, I started having some concerns on if I will be able to keep on reflecting on the ethical aspects of my work now that my work has become more pragmatic and my autonomy has decreased. In general I think we as a data science community are not doing enough to guarantee our work does not harm or disadvantage those that interact with whatever we create. In this piece I tried to consolidate my observations and ideas on how to do better than we are currently doing, by adopting a more human-centric and value-sensitive approach.
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Publication | Data Analytics & AIHow to write amazing code as a Data Scientist
And why you should learn how to do it
Read the full storyPublication | Data Analytics & AI"Must-Have Skills" is Silly
Let's talk about marketing techniques without skill anxiety.
Read the full storyCareer Blog | Data Analytics & AIMachine learning explainability: a hands-on introduction
Machine learning/AI explainability (also called XAI in short) is becoming increasingly popular. As algorithms become more and more prevalent in high-stakes decisions in industries such as finance, healthcare and insurance, the demand for explainability will only grow.
Read the full storyCoding Tutorial | Data Analytics & AIHow I would redo my Data Science journey if I had to start from Scratch
The things I would learn, projects I would do, and skills I would prioritise if I had to learn from scratch
Read the full storyPublication | Data Analytics & AIHow I Hire for Data Science?
As a former CTO in a data science business, I have been asked this question many times. This post outlines the exact method and procedure that I have used. I can not promise you that preparing for this will get you hired anywhere, but this method and procedure did create one of the stronger data science teams that exists. I hope it helps…
Read the full storyCareer Blog | Data Analytics & AIComplexity and Big O Notation: The Ultimate Guide
"In almost every computation, a variety of arrangements for the process is possible. It is essential to choose that arrangement which shall tend to minimise the time necessary for the calculation".
Read the full storyPublication | Software EngineeringData Science Career Summit  — Day 2
On November 18-19th AIgents and the European Leadership University organized the first Data Science Career Summit. The title of this first edition was ‘Building a Data Science Career’. In two days, 14 different talks were presented by Data Science consultants, team leads, entrepreneurs, recruiters and headhunters.
Read the full storyCareer Blog | Data Analytics & AIThe Whys of Transparent Artificial Intelligence (TAI)
"He who has a why to live for can bear almost any how." ― Friedrich Nietzsche
Read the full storyPublication | Data Analytics & AIIntroduction to Convolutional Neural Networks CNNs
Take the first steps in understanding how computer vision works with CNN networks
Read the full storyPublication | Data Analytics & AIData Science Career Summit: ‘Building a Data Science Career’ — Day 1
On November 18-19th AIgents and the European Leadership University organized the first Data Science Career Summit. The title of this first edition was ‘Building a Data Science Career’. In two days, 14 different talks were presented by Data Science consultants, team leads, entrepreneurs, recruiters and headhunters.
Read the full storyCareer Blog | Data Analytics & AIIteratively Finding a Good Machine Learning Model
There is a theorem telling us there is no single machine learning method that performs best in all problems. So how do we find the best one that fits our needs? This post suggests that before going into complex methods and spending time on fine-tuning your deep learning model, try simple ones. As you gear up towards more complex methods, you may find that a simple one is sufficient for your needs.
Read the full storyCase study | Data Analytics & AI5 Skills Data Scientists Should Learn
What Data Scientists don’t learn in online courses or in University? Knowing the basics of these 5 skills will get you ahead in the workplace.
Read the full storyCareer Blog | Data Analytics & AIUnderstanding Data Science Job Titles
Top 4 job roles in the industry that you should know
Read the full storyCareer Blog | Data Analytics & AIDistance Metrics for Machine Learning
The most common Distance Metrics for Machine Learning and how to implement them in Python!
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