datapine

MAY 14, 2019

Best for: Those looking for a practical means of understanding how artificial intelligence serves to enhance data science and use this knowledge to improve their data analytics strategies. 2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. “Machine Learning Yearning” by Andrew Ng.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Smart Data Collective

JANUARY 20, 2020

While marketers have been continually using the best possible strategies to improve the existing global blogging landscape, the inclusion of artificial intelligence has taken the ballgame to a whole different level. It goes without saying that blogging has slowly and steadily evolved into an indispensable marketing tool. Brainstorming Ideas.

Deep Learning 99

Deep Learning ROI Data-driven Marketing 99

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 57

Data mining Machine Learning Deep Learning Marketing 57

CIO Business Intelligence

APRIL 26, 2022

For personnel, cameras look for personal protective equipment (PPE) use, such as hard hats and safety glasses, and then the system either sends alerts to a manager if PPE is not being worn or keeps track of metrics that a safety officer uses to determine whether training is needed. How can we impact manufacturing revenue? .

Manufacturing 98

Manufacturing Optimization Metrics Deep Learning 98

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. The technology’s ability to adapt and learn from interactions further refines customer support metrics, including response time, accuracy of information provided, customer satisfaction and problem-resolution efficiency.

Enterprise 104

Enterprise Interactive Data-driven Key Performance Indicator 104

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. A step-by-step guide to incorporating AI into your marketing strategy Follow these five steps to effectively incorporate AI into your next marketing campaign.

Marketing 84

Marketing Technology Advertising ROI 84

O'Reilly on Data

DECEMBER 12, 2019

If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. That’s where remediation strategies come in. We discuss seven remediation strategies below. You’ve even discovered a few problems with your ML model. What can you do?

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

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

DataRobot Blog

MAY 26, 2022

In this post, we will dive deeper into how members from both the first and second line of defense within a financial institution can adapt their model validation strategies in the context of modern ML methods. Figure 4: DataRobot provides an interactive ROC curve specifying relevant model performance metrics on the bottom right.

Risk 52

Risk Modeling Metrics Business Objectives 52

Insight

OCTOBER 25, 2019

Challenges and Strategies The difficulty of this project is two-fold. The latter is particularly restricting, as it violates the prerequisite of many deep learning methods for image classification?—?a For my project, I decided to try two different strategies to tackle my small data problem?—?one Meta-Learning v.s.

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. Serve : Build cloud services for data products through automation and platform service technology so they can be operated securely at global scale.

Strategy 111

Strategy Cost-Benefit Data-driven Measurement 111

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

Rocket-Powered Data Science

JULY 6, 2021

4) AIOps increasingly became a focus in AI strategy conversations. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all. There was some research published earlier in 2020 that found that traditional, less complex algorithms can be nearly as good or better than deep learning on some tasks.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

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). Deep learning models are usually composed of several functions, stacked together.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

AUGUST 10, 2021

This change makes models the new currency of competitive advantage, strategy, and growth. PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models. Deep Learning: designed to replicate the structure of the human brain.

Modeling 64

Modeling IT Risk Management Deep Learning 64

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

DataKitchen

APRIL 13, 2021

A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications.

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

DECEMBER 20, 2023

To deploy reinforcement learning, an agent takes actions in a specific environment to reach a predetermined goal. The agent is rewarded or penalized for its actions based on an established metric (typically points), encouraging the agent to continue good practices and discard bad ones.

Machine Learning 80

Machine Learning Modeling Deep Learning Predictive Modeling 80

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. It is also suitable for online applications, as the scoring function is usually very lightweight. 0.01, 0.001] }.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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

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. The contents will cover. Defining the agent.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

AWS Big Data

OCTOBER 26, 2023

When running your own proof of concept, it’s important to focus on the right metrics—query throughput (number of queries per hour), response time, and price-performance. You can make a data-driven decision by running a proof of concept on your own or with assistance from AWS or a system integration and consulting partner.

Data Warehouse 103

Data Warehouse Cost-Benefit Dashboards Optimization 103

DataRobot Blog

DECEMBER 20, 2022

Automating and optimizing their investment strategy. By using this model, all accuracy metrics would also comply with national valuation regulations —as defined by the Bank of Spain. Activation Maps allows DataRobot users to see which part of various images the machine learning model is using for making predictions. Conclusions.

Management 59

Management Machine Learning Optimization Modeling 59

Insight

MARCH 28, 2019

Yanxia then used a combination of quantitative and qualitative metrics to interpret each topic group identified by LDA. This approach involved finding context-aware embedding of each word or phrase in a review, then using latent Dirichlet allocation (LDA) to identify how words correspond to latent topic distributions.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

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