Smart Data Collective

JUNE 4, 2021

Probability is the measurement of the likelihood of events. Similarly, when a user watches a movie from a series, the video hosting application recommends other movies from the series. Deep Learning. Deep learning is a subset of machine learning that works similar to the biological brain. Probability.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. Will it be implemented on-premises or hosted using a cloud platform? AI plays a pivotal role as a catalyst in the new era of technological advancement.

Machine Learning 74

Machine Learning Manufacturing Cost-Benefit Deep Learning 74

Smart Data Collective

FEBRUARY 20, 2022

AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms. Also, developers can connect GPU clusters or compute-optimized instances to AWS Deep Learning Amazon Machine Images (AMIs) to create and train custom AI models. Messages and notification. Easy to use.

Cost-Benefit 115

Cost-Benefit Data Lake Software Machine Learning 115

Cloudera

SEPTEMBER 20, 2022

The state of the art in AI systems for artistic tasks almost universally use deep-learning models, which presuppose a significant amount of compute resources both to create them, and once created to continue to use them for producing images. Access — who can use it? Data — where does it come from? Conclusion.

Deep Learning 87

Deep Learning Cost-Benefit Risk Data-driven 87

O'Reilly on Data

DECEMBER 12, 2019

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. 8] , [12] Again, traditional model assessment measures don’t tell us much about whether a model is secure. Residual analysis.

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

Smart Data Collective

MAY 17, 2021

A mission-critical task like maintenance can be relegated to proactive measures thanks to a steady flow of performance data. What’s more, the same technology can be used for other measures, like monitoring assets and goods, which cuts down on fraud and theft. There are also a host of new challenges, the pandemic being only one of them.

Big Data 100

Big Data Cost-Benefit IoT Machine Learning 100

CIO Business Intelligence

JANUARY 4, 2023

Recently members of our community came together for a roundtable discussion, hosted by Dell Technologies, about trends, trials, and all the excitement around what’s next. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Cost-Benefit 57

Cost-Benefit Machine Learning Modeling Uncertainty 57

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Managing Machine Learning Projects” (AWS).

Management 327

Management Machine Learning Experimentation Metrics 327

IBM Big Data Hub

APRIL 18, 2024

According to Andreessen Horowitz (link resides outside IBM.com ) , in 2023, the average spend on foundation model application programming interfaces (APIs), self-hosting and fine-tuning models across surveyed companies reached USD 7 million.

Cost-Benefit 92

Cost-Benefit Modeling Manufacturing Interactive 92

DataRobot Blog

MAY 26, 2022

However, with the widespread adoption of modern ML techniques, including gradient-boosted decision trees (GBDTs) and deep learning algorithms , many traditional validation techniques become difficult or impossible to apply.

Risk 52

Risk Modeling Metrics Business Objectives 52

Insight

MARCH 25, 2020

After reading this, I hope you can learn how to build deep learning models using TensorFlow Keras, productionalize the model as a Streamlit app, and deploy it as a Docker container on Google Cloud Platform (GCP) using Google Kubernetes Engines (GKE). In this project, I was curious to see if deep learning approaches?—?specifically

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Domino Data Lab

MAY 8, 2019

Machine learning model interpretability. At CMU I joined a panel hosted by Zachary Lipton where someone in the audience asked a question about machine learning model interpretation. measure the subjects’ ability to trust the models’ results. Let’s look through some antidotes. Generally, you cannot get both.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

APRIL 3, 2019

Fun fact : I co-founded an e-commerce company (realistically, a mail-order catalog hosted online) in December 1992 using one of those internetworking applications called Gopher , which was vaguely popular at the time. Edge caches become crucial for managing data on its way from web servers to mobile devices. credit cards). Upcoming Events.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Occam's Razor

OCTOBER 12, 2017

Ask them what they worry about, ask them what they are solving for, ask them how they measure success, ask them what are two things on the horizon that they are excited about. The Future of Life Institute hosted a conference in Asilomar in Jan 2017 with just such a purpose. Intro to Machine Learning. Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136