IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. But for most enterprise, using machine learning…not really. You see these drivers involving risk and cost, but also opportunity.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? The program supports hands-on data science class sizes of more than 1,200 students based on JupyterHub , and this sets a bar for enterprise infrastructure. In business terms, why does this matter ? Translated: MOOCs are no panacea.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Domino Data Lab

AUGUST 8, 2019

There’s been a flurry of tech startups, open source frameworks, enterprise products, etc., Consider the following timeline: 2001 – Physics grad students are getting hired in quantity by hedge funds to work on Wall St. The probabilistic nature changes the risks and process required. It’s a quick way to clear the room.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71