In my last blog post, I talked about the importance of establishing the right team for data science projects. Here, I’m going to talk about some of the barriers that can prevent successful adoption of data science. You can read my whole "data science in the wild" blog series here.
Detecting malpractice and crime – whether it is fraud, people smuggling, avoiding customs or organised crime – is a complex process. Detection is all very well and a necessary step. But what are the outcomes that your organisation needs? And what workflows and triggers do you need in place to
Interview mit Bundesministerium für Wirtschaft und Energie, Leiter der Stabsstelle für KI: Marco-Alexander Breit.
Der Einsatz einer zentralen, skalierbaren Plattform, die offen, flexibel und jederzeit anpassbar ist, kann Kassen der Steuerbehörden unterstützen.
You’ve finally done it. You managed to stay awake through the endless series of MOOC videos, and you’ve mastered the IRIS data set. You've learned that lm() will build you a pretty nifty model in R, and you can fit a Classifier with SciKit Learn. You know your Neural Net
The pandemic has done more to drive consumer adoption of online channels than any digital transformation initiative – but companies should be careful what they wish for. 2020 has been a difficult year for everyone, and as the coronavirus continues to impact lives, health and the economy, it would be
Zorlu Son Aşama: Model İmplementasyonu Günümüzde neredeyse tüm organizasyonların iş kararları vermek için, veriden faydalanarak gerçek zamanlı içgörüler elde etmeye çalıştığı bir dijital yolculuk içerisinde olduklarını görüyoruz. Sınırlarını hayalgücümüzün ve yeteneklerimizin belirlediği veri analitiği bizlere sonsuz bir potansiyel sunuyor. 2019 yılında analitik yazılımlara 190 milyar Dolar yatırım yapılması da şirketlerin
The companies I usually deal with, especially healthy and successful ones, often don’t believe that they need to change. However, I think this is where problems take root. I believe changes should be made when things are going well because when they have gone wrong, it's too late. You no
A global teaching resource for post-COVID-19 academia During the COVID-19 pandemic, governments used data science modelling to justify actions around lockdowns, and then again, in due course, when they eased restrictions. These actions affected billions of citizens’ lives and livelihoods. The importance of analytical calculation and competence was brought home,
A prima vista, potrebbe sembrare che data science e psicologia abbiano ben poco in comune. Tuttavia, di recente ho iniziato ad appassionarmi di psicologia e penso che tra le due ci siano molte più somiglianze di quanto si possa pensare. 1. Sia Data Science che psicologia ci aiutano a rispondere
