CIO Business Intelligence

JUNE 21, 2022

In addition to quantitative ROI metrics, HPC research was also shown to save lives, lead to important public/private partnerships, and spur innovations. . Real-time big data analytics, deep learning, and modeling and simulation are newer uses of HPC that governments are embracing for a variety of applications. HPC Growth in U.S.

Deep Learning 111

Deep Learning Big Data ROI Software 111

CIO Business Intelligence

APRIL 26, 2022

Ever increasing advances in technology and continuous process optimization techniques have helped ensure that the global supply chain runs efficiently, turning raw materials into products that make their way to physical stores and ecommerce warehouses. How can we positively impact the employee or “people” experience?

Manufacturing 98

Manufacturing Optimization Metrics Deep Learning 98

CIO Business Intelligence

JUNE 1, 2022

Aside from monitoring components over time, sensors also capture aerodynamics, tire pressure, handling in different types of terrain, and many other metrics. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use.

Manufacturing 119

Manufacturing Digital Transformation Predictive Analytics Strategy 119

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 104

Enterprise Interactive Data-driven Key Performance Indicator 104

DataRobot

OCTOBER 20, 2021

rule-based AI , machine learning , deep learning , etc.) Evaluation metrics for machine learning models: Understanding evaluation metrics, what they optimize for, and how they intersect with AI fairness principles gives stakeholders the language necessary to qualify risks associated with AI systems.

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

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 84

Marketing Technology Advertising ROI 84

O'Reilly on Data

MARCH 31, 2020

At measurement-obsessed companies, every part of their product experience is quantified and adjusted to optimize user experience. They have deployed machine learning at scale to recommend movies and friends, personalize ads, and deliver search results. Even if a product is feasible, that’s not the same as product-market fit.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

AUGUST 11, 2023

MLOps is the next evolution of data analysis and deep learning. Simply put, MLOps uses machine learning to make machine learning more efficient. Each data attribute, or feature, is managed within a feature store and can be added, deleted, combined or adjusted to improve the machine learning model.

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. Python is the most common programming language used in machine learning.

Machine Learning 58

Machine Learning Data Science Statistics Deep Learning 58

IBM Big Data Hub

AUGUST 28, 2023

Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification. A targeted approach will optimize the user experience and enhance an organization’s ROI.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

CIO Business Intelligence

JANUARY 4, 2023

Workflow Optimization from Edge to Core/Cloud and Back : Integration with edge devices as well as integration with different HPC systems is currently designed in-house or otherwise customized. Of course, data center challenges are also driving demand for these alternatives. Just starting out with analytics?

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Domino Data Lab

JULY 28, 2021

Communication cannot be emphasized enough, for it is this trait that ensures results are effectively translated from the white board to impact on business metrics. In fact, deep learning was first described theoretically in 1943. Reinforcement learning focuses on optimizing a specific decision.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Insight

JANUARY 14, 2020

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. Choosing your loss function and optimizer Finally, in the last block of code, we must compile the model that we just built.

Metrics 58

Metrics Optimization Modeling Testing 58

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). Then, it can tailor marketing materials to match those interests.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Cloudera

FEBRUARY 16, 2022

By logging the performance of every combination of search parameters within an experiment, we can choose the optimal set of parameters when building a model. Given the complexity of some ML models, especially those based on Deep Learning (DL) Convolutional Neural Networks (CNNs), there are limits to interpretability.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

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

Edwin Chen

OCTOBER 6, 2014

Click-through rate may be your initial hope…but after a bit of thought, it's not clear that it's the best metric after all. Metrics like CTR, or even number of favorites and retweets, will probably optimize for showing quick one-liners and pictures of funny cats. Amazon, and Moving Beyond Log-Based Metrics.

Metrics 79

Metrics Measurement Machine Learning Testing 79

Domino Data Lab

APRIL 29, 2021

Deep learning enthusiasts are increasingly putting NVIDIA’s GTC at the top of their gotta-be-there conference list. Three of them were particularly compelling and inspired a new point of view on transfer learning that I feel is important for analytical practitioners and leaders to understand. Deep Learning Trends from GTC21.

Data Science 134

Data Science Deep Learning Modeling Forecasting 134

Domino Data Lab

FEBRUARY 10, 2019

Metrics can also increase a lot in the early days of a project and then suddenly hit a wall. Humans likely not even notice the difference but modern deep learning networks suffered a lot. On Twitter, two humans might only agree on the sentiment of a tweet 80% of the time. Images off the web tend to frame the object in question.

Machine Learning 63

Machine Learning Modeling Deep Learning Metrics 63

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. 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

DataRobot Blog

APRIL 22, 2022

In our previous post , we talked about how red AI means adding computational power to “buy” more accurate models in machine learning , and especially in deep learning. This view actually delivers four out of the five efficiency metrics that we discussed in the previous blog post.

Machine Learning 98

Machine Learning Measurement Deep Learning Manufacturing 98

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

The first is that they are straightforward to optimize using traditional gradient-based optimizers as long as we pre-specify the placement of the knots. There is a robust set of tools for working with these kinds of constrained optimization problems. Other deep learning models can also be written in this form.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. There needs to be a way to validate this against a given metric and validation set before deploying a model.

Modeling 194

Modeling Machine Learning Testing Metrics 194

DataKitchen

APRIL 13, 2021

Observe, optimize, and scale enterprise data pipelines. . A complete DataOps program will have a unified, system-wide view of process metrics using a common data store. DataMo – Datmo tools help you seamlessly deploy and manage models in a scalable, reliable, and cost-optimized way. Monte Carlo Data — Data reliability delivered.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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 103

Data Warehouse Cost-Benefit Dashboards Optimization 103

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 80

Machine Learning Modeling Deep Learning Predictive Modeling 80

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. First, we define a function that will perform a grid search for the optimal hyperparameters of the classifier. Selecting the optimal threshold value can be performed in a number of ways. from imblearn.over_sampling import SMOTE.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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 111

Strategy Cost-Benefit Data-driven Measurement 111

Domino Data Lab

JULY 22, 2019

and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. They’d like to do something more efficient when they’re training a lot of deep learning models. Machine learning is a subset of mathematical optimization.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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

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

MAY 8, 2019

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. If your “performance” metrics are focused on predictive power, then you’ll probably end up with more complex models, and consequently less interpretable ones.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Business Over Broadway

DECEMBER 20, 2018

Predictive analytics and artificial intelligence capabilities provide a way to extract insights from that data to help you improve the customer experience and optimize customer loyalty. Looking ahead to 2018, data professionals are most interested in learning deep learning (41%).

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74