IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. MLOps and IBM Watsonx.ai

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

O'Reilly on Data

APRIL 19, 2021

First, 82% of the respondents are using supervised learning, and 67% are using deep learning. Deep learning is a set of algorithms that are common to almost all AI approaches, so this overlap isn’t surprising. 58% claimed to be using unsupervised learning. Techniques.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. In fact, deep learning was first described theoretically in 1943.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

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

DataRobot

NOVEMBER 9, 2021

Signal classification models are typically built using time series principles; traditionally used features that include central, windowed, lag, and lead statistics can do the job but sometimes there might be scenarios where we want to eke out more performance out of the data. Image courtesy towardsAI.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

Smarten

APRIL 19, 2024

Anomaly Alerts KPI monitoring and Auto Insights allows business users to quickly establish KPIs and target metrics and identify the Key Influencers and variables for the target KPI.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. To deploy reinforcement learning, an agent takes actions in a specific environment to reach a predetermined goal.

Machine Learning 81

Machine Learning Modeling Deep Learning Predictive Modeling 81

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. You can take TensorFlow.js

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. More knots make the learned feature transformation smoother and more capable of approximating any monotonic function.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management 110

Management Machine Learning Experimentation Metrics 110