O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. 15] Organizations should, if possible, require that all important data science projects include personnel with expertise in ethics, privacy, social sciences, or other related disciplines.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

O'Reilly on Data

FEBRUARY 18, 2020

Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%. In 2019, as in 2018, Python was the most popular language on O’Reilly online learning.

Data-driven 335

Data-driven Software Statistics Marketing 335

KDnuggets

OCTOBER 31, 2019

These results will go into each each region and employment type to find out the differences and similarities especially between people from Industry and Students.

Data Science 46

Data Science Deep Learning Statistics Machine Learning 46

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Acquired by DataRobot June 2019).

Testing 307

Testing Machine Learning Consulting Data Quality 307

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

A more general approach is to learn a Generalized Additive Model (GAM). GAMs are popular among data science and machine learning applications for their simplicity and interpretability. Monotonic Deep Lattice Networks Deep learning is a powerful tool when we have an abundance of data to learn from.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Machine learning model interpretability. ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. Here are some open-source options to consider.

Data Science 68

Data Science Machine Learning Big Data Interactive 68

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

OCTOBER 9, 2019

Data Science meets Climate Science. Environment Data Management (EDM) is an annual meeting for data management teams at the NOAA , this year chaired by Kim Valentine and Eugene Burger. Data veracity, data stewardship, and heros of data science. AI CA 2019 highlights.

Deep Learning 69

Deep Learning Metadata Machine Learning Data Science 69

BizAcuity

MARCH 31, 2022

By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. of organizations who participated in an executive survey back in 2019 claimed they are going to be investing in big data and AI. Source: Gartner Research). Source: TCS).

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Business Over Broadway

DECEMBER 20, 2018

The importance of data science and machine learning continues to grow in business and beyond. I did my part this year to spread interest in data science to more people. Below are my top 10 blog posts of 2018: Favorite Data Science Blogs, Podcasts and Newsletters. Click image to enlarge.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. Next let’s use the displaCy library to visualize the parse tree for that sentence: In [4]: from spacy import displacy?? Usually it’s human-generated text, but not always.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110