IBM Big Data Hub

SEPTEMBER 6, 2023

Search engine optimization (SEO): Deploying an AI solution to enhance search engine optimization (SEO) helps marketers increase page rankings and develop more sound strategies. AI can help marketers create and optimize content to meet the new standards.

Marketing 78

Marketing Technology Advertising ROI 78

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. It signifies a shift in human-digital interaction, offering enterprises innovative ways to engage with their audience, optimize operations, and further personalize their customer experience. billion by 2030.

Enterprise 95

Enterprise Interactive Data-driven Key Performance Indicator 95

IBM Big Data Hub

AUGUST 28, 2023

With nearly 5 billion users worldwide—more than 60% of the global population —social media platforms have become a vast source of data that businesses can leverage for improved customer satisfaction, better marketing strategies and faster overall business growth.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

When these concerns loom too large to ignore, data scientists and practitioners will generally adopt one of a few suboptimal strategies. First, they might throw up their hands and pursue a non-machine-learned solution (say, some trusty if-statements). TF Lattice uses piecewise-linear functions (PLFs) in its feature transformations.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

AWS Big Data

OCTOBER 26, 2023

Some recent examples of performance optimizations driven by fleet telemetry include: String query optimizations – By analyzing how Amazon Redshift processed different data types in the Redshift fleet, we found that optimizing string-heavy queries would bring significant benefit to our customers’ workloads.

Data Warehouse 95

Data Warehouse Cost-Benefit Dashboards Optimization 95

CIO Business Intelligence

JANUARY 4, 2023

Scaling out and developing large-scale systems : To meet demand, the HPC industry is developing and honing strategies to effectively scale and deploy large systems that are both efficient and reliable. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. Essential Theory of Reinforcement Learning.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

Domino Data Lab

APRIL 21, 2021

deep learning) there is no guaranteed explainability. from sklearn import metrics. There are different approaches to this strategy, with the two most commonly used being random oversampling and SMOTE. First, we define a function that will perform a grid search for the optimal hyperparameters of the classifier.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Insight

JANUARY 14, 2020

I was familiar with the strategy of using data augmentation techniques (such as flipping, shearing, zooming, etc.) Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow. What the heck!

Metrics 58

Metrics Optimization Modeling Testing 58

O'Reilly on Data

JANUARY 25, 2021

We don’t see that in our data, though there are certainly some metrics to say that artificial intelligence has stalled. A backlash is only to be expected when deep learning applications are used to justify arresting the wrong people , and when some police departments are comfortable using software with a 98% false positive rate.

Machine Learning 363

Machine Learning Software Testing Technology 363

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

IBM Big Data Hub

NOVEMBER 14, 2023

Internal data monetization initiatives measure improvement in process design, task guidance and optimization of data used in the organization’s product or service offerings. Realize: Instrument the data product services to enable adherence to risk and compliance controls with event and metrics data integrated to financial management.

Strategy 104

Strategy Cost-Benefit Data-driven Measurement 104

Insight

MARCH 28, 2019

Yanxia then used a combination of quantitative and qualitative metrics to interpret each topic group identified by LDA. in mathematics from the University of Illinois at Urbana-Champaign, where he discovered techniques for finding optimal paths between points in constrained spaces. Yanxia Li earned her Ph.D.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

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 74

Machine Learning Modeling Deep Learning Predictive Modeling 74

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