IBM Big Data Hub

JULY 6, 2023

An online hospitality company uses data science to ensure diversity in its hiring practices, improve search capabilities and determine host preferences, among other meaningful insights. The evolution of machine learning The start of machine learning, and the name itself, came about in the 1950s.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

DataKitchen

APRIL 13, 2021

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Testing and Data Observability. Production Monitoring and Development Testing.

Testing 307

Testing Machine Learning Consulting Data Quality 307

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Managing Machine Learning Projects” (AWS).

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

SEPTEMBER 12, 2018

AbbVie’s platform uses analytics and machine learning, including natural language processing, deep learning, and unsupervised learning, to proactively identify issues and opportunities. Brian Carpenter , Co-Host, The Hot Aisle Podcast, @intheDC. Cloud Success: . FairVentures Lab (nominated by Cazena ).

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Domino Data Lab

JULY 2, 2019

SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Software writes Software?

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

DataRobot Blog

DECEMBER 20, 2022

In this context, an augmented intelligence approach around the data will be increasingly more critical for asset managers, investors, and real estate developers to ensure a better understanding of the real estate assets and take better decisions aimed at optimizing both the Net Asset Value and the Net Operating Income.

Management 59

Management Machine Learning Optimization Modeling 59

Domino Data Lab

MARCH 29, 2021

Maintaining the cluster and the underlying infrastructure configuration can be a complex and time-consuming task Lack of GPU acceleration – Complex machine workloads, especially the ones involving Deep Learning, benefit from GPU architectures that are well adapted for vector and matrix operations. GPU) and use bitnami/spark:2.4.6

Cost-Benefit 98

Cost-Benefit Machine Learning Testing Interactive 98

Domino Data Lab

JANUARY 14, 2019

The notebook is hosted on Domino’s trial site. Let’s build the models that we’ll use to test SHAP and LIME. xgb_model = xgb.train({'objective':'reg:linear'}, xgb.DMatrix(X_train, label=y_train)) # GBT from scikit-learn? To keep it simple, I choose to explain the first record in the test set for each model using SHAP and LIME. #

Testing 89

Testing Modeling Deep Learning Data Science 89

Domino Data Lab

MAY 8, 2019

Machine learning model interpretability. At CMU I joined a panel hosted by Zachary Lipton where someone in the audience asked a question about machine learning model interpretation. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JULY 9, 2019

He advocated that an impactful ML solution does not end with Google Slides but becomes “a working API that is hosted or a GUI or some piece of working code that people can put to work” Wiggins also dove into examples of applying unsupervised, supervised, and reinforcement learning to address business problems.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

JANUARY 25, 2021

Both SRE and DevOps emphasize similar practices: version control (62% growth for GitHub, and 48% for Git), testing (high usage, though no year-over-year growth), continuous deployment (down 20%), monitoring (up 9%), and observability (up 128%). It’s particularly difficult if testing includes issues like fairness and bias.

Machine Learning 363

Machine Learning Software Testing Technology 363

Occam's Razor

OCTOBER 12, 2017

When you go to the interview, the hiring company will proceed to ask questions that test your competency in the listed job requirements. Test for analytics experience AND explore the level of analytical thinking the job candidate possesses. Optimal Starting SCOTUS Starting Points. Intro to Machine Learning. Deep Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136