datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. There are various procurement KPIs , but keeping them fluent, cohesive, efficient, and consistent is key to your success – if one domino in the chain falls, so will most of the others.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Domino Data Lab

MAY 1, 2019

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Special thanks to Mawer for the permission to excerpt the slides in this Domino Data Science Field Note. Introduction. test_size: 0.25

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

Domino Data Lab

JANUARY 20, 2019

The MLConf talk is based on a paper Kim co-authored and the code is available. This blog post provided distilled highlights and excerpts from recent research on TCAV. If interested additional insights, please refer to the following resources that were referenced and reviewed during the writing of this blog post. Introduction.

Testing 63

Testing Modeling Machine Learning Data Science 63

Cloudera

MARCH 2, 2022

Stress tests conducted by authorities such as the Federal Reserve Bank in the US are designed to keenly monitor the financial stability of the banking sector, especially during economic downturns such as those brought on by the pandemic. The post Manage the Demand of Stress Testing in Financial Services appeared first on Cloudera Blog.

Testing 95

Testing Management Risk Management Forecasting 95

Domino Data Lab

JUNE 13, 2019

Visually examine the poorest matches, trying to understand what the MNIST authors could have done differently to justify these differences without at the same time changing the existing close matches. Use the Hungarian algorithm to find the best pairwise match between the MNIST training digits and our reconstructed training digits.

Testing 83

Testing Data Science Experimentation Metadata 83

Domino Data Lab

JANUARY 14, 2019

This blog post provides insights on how to use the SHAP and LIME Python libraries in practice and how to interpret their output, helping readers prepare to produce model explanations in their own work. The notebook is hosted on Domino’s trial site. import os #needed to use Environment Variables in Domino? Introduction.

Testing 89

Testing Deep Learning Modeling Data Science 89

Domino Data Lab

AUGUST 12, 2021

In a previous blog , we have covered how Pandas Profiling can supercharge the data exploration required to bring our data into a predictive modelling phase. Please note that this may not be the actual intention of the original authors of the dataset. However, it provides us with some cleaning steps we can carry out for this exercise.

Machine Learning 126

Machine Learning Reporting Statistics Visualization 126

Domino Data Lab

JULY 28, 2021

That’s what Domino’s Enterprise MLOps platform delivers. That’s why Domino’s workbench provides a notebook-based environment where data scientists can collaborate, share knowledge and perform all their model R&D in one place. Silos Are Demolished. Breaking down silos are key for scaling data science.

Data Science 59

Data Science Enterprise Cost-Benefit Data-driven 59

Domino Data Lab

OCTOBER 7, 2020

In this blog we show what the changes in behavior of data are in high dimensions. In our next blog we discuss how we try to avoid these problems in applied data analysis of high dimensional data. Finally, our analysts deploy the developed custom statistical software in client pipelines and within Domino environments.

Statistics 145

Statistics Testing Predictive Modeling Big Data 145

Domino Data Lab

JULY 28, 2021

The Workbench is Domino’s notebook-based environment where data scientists can do their R&D and experimentation. David Weedmark is a published author who has worked as a project manager, software developer, and as a network security consultant. Have a question? Get in touch with us.

Data Science 59

Data Science Enterprise Modeling Experimentation 59

Domino Data Lab

JULY 19, 2021

David Weedmark is a published author who has worked as a project manager, software developer, and as a network security consultant. The post 7 Key Roles and Responsibilities in Enterprise MLOps appeared first on Data Science Blog by Domino. To evaluate it for yourself, register for a free 2-week trial.

Enterprise 85

Enterprise Data Science Testing Modeling 85

Domino Data Lab

DECEMBER 2, 2020

In this blog post, I will cover a family of techniques known as density-based clustering. As always, the code can be found on the Domino platform. You’ll need to sign up to run the code for free in Domino. For this section, I will be using the denpro R package, developed by professor and author, Jussi Klemela. Level Sets.

Metrics 116

Metrics KDD Testing Machine Learning 116

Domino Data Lab

AUGUST 6, 2021

David Weedmark is a published author who has worked as a project manager, software developer, and as a network security consultant. The post Adopting the 4 Step Data Science Lifecycle for Data Science Projects appeared first on Data Science Blog by Domino. To evaluate it for yourself, register for a free 2-week trial.

Data Science 75

Data Science Testing Modeling Publishing 75

bridgei2i

JUNE 11, 2020

So we see a lot of new delivery channels being explored, e.g. tie-ups with food delivery platforms like Zomato, Swiggy and chains like Dominoes Pizza in India, as well as D2C models. Authors: Jagriti Khiste & Siddhesh Kharode. Distribution channels, especially in emerging markets, are severely strained economically. Take a look.

Digital Transformation 52

Digital Transformation Sales Uncertainty Forecasting 52

Domino Data Lab

AUGUST 10, 2021

This can be done automatically using the Domino Model Monitor platform by specifying model accuracy metrics and then having the platform notify you if the model performs outside of those metrics. David Weedmark is a published author who has worked as a project manager, software developer, and as a network security consultant.

Modeling 64

Modeling IT Deep Learning Risk Management 64

Domino Data Lab

APRIL 24, 2019

This blog post provides insights on how to apply Natural Language Processing (NLP) techniques. A complementary Domino project is available. In this blog post, we address the question: “ Can data science help us make sense of the Mueller Report?” The Mueller Report. Applying Natural Language Processing (NLP).

Data Science 106

Data Science Reporting Analytics Machine Learning 106