DataRobot

FEBRUARY 10, 2021

Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD by Jeremy Howard and Sylvain Gugger is a hands-on guide that helps people with little math background understand and use deep learning quickly. The following figure shows the Python code and how it led to data after November 2011.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

DataRobot Blog

MAY 26, 2022

When the FRB’s guidance was first introduced in 2011, modelers often employed traditional regression -based models for their business needs. This may be accomplished through a wide variety of tests, to develop a deeper introspection into how the model behaves. Conclusion.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

APRIL 3, 2019

Fun fact: in 2011 Google bought remnants of what had previously been Motorola. We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks. Does machine learning change priorities? In short, the virtuous cycle is growing.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

MARCH 3, 2019

I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms. The data types used in deep learning are interesting. The data types used in deep learning are interesting. One-fifth use reinforcement learning. Or something. Technologies.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

O'Reilly on Data

MAY 21, 2019

Consider deep learning, a specific form of machine learning that resurfaced in 2011/2012 due to record-setting models in speech and computer vision. A typical data pipeline for machine learning. If anything, deep learning models are even more data hungry than previous algorithms favored by data scientists.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Domino Data Lab

JULY 9, 2019

A “data scientist” might build a multistage processing pipeline in Python, design a hypothesis test, perform a regression analysis over data samples with R, design and implement an algorithm in Hadoop, or communicate the results of our analyses to other members of the organization in a clear and concise fashion.

Data Science 112

Data Science Machine Learning Advertising Modeling 112