18 Analytics Tools Every Business Manager Should Know


The goal of any business analytic tool is to analyze data and extract actionable and commercially relevant information that you can use to increase results or performance. But with so many tools available it can be difficult to know what to use and when. I thought it might be useful to look at some of the…

18+1 Tendencias de Big Data Science para 2018


En esta época del año, los profesionales del sector solemos buscar las Tendencias (que a mi me gusta llamarlas también predicciones) para el próximo año 2018. El blog @noeliagorod no va ha ser diferente, y como el próximo año nuevo termina en 18 mencionaré las 18 tendencias a nivel mundial en Data Science, aquí vamos: Uso masivo de…

AI and ML in 2017


The advancement of machine learning and artificial intelligence is opening new doors for businesses to make more data-driven decisions at higher accuracy rates. Data and analytics are also changing the way that businesses compete. As leading companies take advantage of the power of big data, and laggards stay behind, the disparity between the two groups…

Open Source Deep Learning Frameworks and Visual Analytics


Deep Learning gets more and more traction. It basically focuses on one section of Machine Learning: Artificial Neural Networks. This article explains why Deep Learning is a game changer in analytics, when to use it, and how Visual Analytics allows business analysts to leverage the analytic models built by a (citizen) data scientist. Post HERE…

Infographic – Quick Guide to learn Python for Data Science


A situation has been described below. Has it ever happened to you? I wanted to learn Python for Data Science, so I googled ‘I want to learn Python for data science’. Google, effortlessly, provided you the link of all resources to learn Python. Then, you get bemused by the innumerable links available to learn Python. Eventually, you…

Common Probability Distributions: The Data Scientist’s Crib Sheet


Data scientists have hundreds of probability distributions from which to choose. Where to start? Data science, whatever it may be, remains a big deal.  “A data scientist is better at statistics than any software engineer,” you may overhear a pundit say, at your local tech get-togethers and hackathons. The applied mathematicians have their revenge, because statistics hasn’t…