Domino Data Lab

JULY 10, 2019

New tools are constantly being added to the deep learning ecosystem. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow data scientists to speed up research.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

Cloudera

APRIL 19, 2021

In our previous blog post in this series , we explored the benefits of using GPUs for data science workflows, and demonstrated how to set up sessions in Cloudera Machine Learning (CML) to access NVIDIA GPUs for accelerating Machine Learning Projects. Now we can run the rest of the script and watch our model train.

Deep Learning 70

Deep Learning Machine Learning Data Science Modeling 70

KDnuggets

AUGUST 1, 2019

This blog explores how to navigate these challenges. Getting trained neural networks to be deployed in applications and services can pose challenges for infrastructure managers. Challenges like multiple frameworks, underutilized infrastructure and lack of standard implementations can even cause AI projects to fail.

Deep Learning 106

Deep Learning Modeling Management 106

AWS Big Data

JUNE 1, 2023

The Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. In this blog post, we demonstrate how you can use DJL within Kinesis Data Analytics for Apache Flink for real-time machine learning inference. The model has been pre-trained on ImageNet with 1.2

Deep Learning 61

Deep Learning Data Analytics Analytics Machine Learning 61

Domino Data Lab

JUNE 14, 2022

In this blog post we share our experience from the BMS molecular translation challenge and show that CPU-based distributed learning can significantly shorten model training times.

Deep Learning 105

Deep Learning Modeling IT Machine Learning 105

Rocket-Powered Data Science

JULY 6, 2023

These AI applications are essentially deep machine learning models that are trained on hundreds of gigabytes of text and that can provide detailed, grammatically correct, and “mostly accurate” text responses to user inputs (questions, requests, or queries, which are called prompts). Guess what? It isn’t.

Statistics 151

Statistics Deep Learning Machine Learning Modeling 151

Dataiku

OCTOBER 4, 2021

Using RNNs & DeepAR Models to Find Out. Time series forecasting use cases are certainly the most common time series use cases, as they can be found in all types of industries and in various contexts.

Forecasting 138

Forecasting Deep Learning IT Sales 138

CIO Business Intelligence

SEPTEMBER 29, 2023

These skills include expertise in areas such as text preprocessing, tokenization, topic modeling, stop word removal, text classification, keyword extraction, speech tagging, sentiment analysis, text generation, emotion analysis, language modeling, and much more.

Deep Learning 143

Deep Learning Machine Learning Modeling Consulting 143

Domino Data Lab

JUNE 13, 2022

In this blog post we share our experience from the BMS molecular translation challenge and show that CPU-based distributed learning can significantly shorten model training times.

Deep Learning 52

Deep Learning Modeling IT Machine Learning 52

Insight

SEPTEMBER 20, 2019

In this blog, I’ll describe how this project uses segmentation to detect lesions in an image, and classification to detect whether those lesions are benign or malignant. The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. Here, we built a model to mimic this process.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

IBM Big Data Hub

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. And then you need highly specialized, expensive and difficult to find skills to work the magic of training an AI model. But that’s all changing thanks to pre-trained, open source foundation models.

Modeling 93

Modeling Data Lake Enterprise Deep Learning 93

Dataiku

JUNE 3, 2022

From marketing to social science to biology, they have been widely promoted as the new way of learning “smartly” from data. It’s more than a trend, though, as many research papers have proven that they can actually lead to more accurate and robust models.

Deep Learning 75

Deep Learning Marketing Modeling 75

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

Domino Data Lab

JULY 17, 2021

The system here will identify, via some meaningful sense, which existing speakers’ model does the utterance match. If the unknown utterance is spoken by a speaker outside the list of existing speakers, the model will nonetheless map it to some speaker from that list. It determines whether the individual is who they claim to be.

Modeling 64

Modeling Testing Machine Learning Measurement 64

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

Dataiku

MARCH 25, 2024

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. But instead, a machine seamlessly identifies the scene and its location, provides a detailed description, and even suggests nearby attractions.

Visualization 132

Visualization Modeling Experimentation Testing 132

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

Deep Learning 72

Deep Learning Experimentation Machine Learning Risk 72

Cloudera

APRIL 10, 2021

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks.

Machine Learning 61

Machine Learning Modeling Cost-Benefit Data Science 61

Data Science 101

NOVEMBER 29, 2019

Amazon Athena and Aurora add support for ML in SQL Queries You can now invoke Machine Learning models right from your SQL Queries. You can choose from the built-in models provided by Amazon SageMaker, or you can use your own models which have been trained and deployed with SageMaker.

Data Science 115

Data Science Deep Learning Machine Learning Modeling 115

Domino Data Lab

DECEMBER 3, 2021

Whether you are a machine learning enthusiast, or a ninja data scientist training models for all sorts of applications, you may have heard of the need to use graphical processing units (GPUs) , to squeeze the best performance when training and scaling your models.

Machine Learning 72

Machine Learning Deep Learning Modeling 72

Analytics Vidhya

SEPTEMBER 13, 2023

This blog is about “Artificial Intelligence and the Aesthetics of Image Generation,” it looks into the technical aspects of AI-powered artistic expression like Neural Style Transfer and Generative Adversarial Networks (GANs).

Technology 312

Technology Analytics IT Deep Learning 312

Domino Data Lab

JANUARY 20, 2019

What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? Using high-level concepts is potentially useful when translating seemingly black box models to stakeholders that are not experts in ML. Introduction. TCAV Github.

Testing 63

Testing Modeling Machine Learning Data Science 63

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

Experimentation 82

Experimentation Modeling Deep Learning Data-driven 82

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. Data must be laboriously collected, curated, and labeled with task-specific annotations to train AI models. We stand on the frontier of an AI revolution.

Enterprise 134

Enterprise Technology Modeling Cost-Benefit 134

IBM Big Data Hub

MAY 9, 2023

By empowering employees with automation and AI technologies like machine learning , deep learning , and natural language processing , IT organizations can narrow skills gaps and enable developers to write quality code with greater efficiency. Powered by IBM watsonx.ai This statement replaces all prior statements on this topic.

IT 93

IT Deep Learning Machine Learning Modeling 93

bridgei2i

JULY 14, 2021

Three Tips For Choosing The Right AI Business Model. The omnipresence of AI is creating new business models which differ starkly from the traditional ones. As a result, companies are exploring the potential of AI to re-write their business models to bring in growth and innovation. Choose The Right Vendor.

Modeling 52

Modeling Deep Learning Enterprise Software 52

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task.

Enterprise 125

Enterprise Modeling Testing Data-driven 125

IBM Big Data Hub

JANUARY 11, 2024

Overcoming the limitations of generative AI We’ve seen numerous hypes around generative AI (or GenAI) lately due to the widespread availability of large language models (LLMs) like ChatGPT and consumer-grade visual AI image generators. Fortunately, production-oriented AI research was going on for years before ChatGPT arrived.

Digital Transformation 109

Digital Transformation Modeling Deep Learning Visualization 109

Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. This blog post hopes to provide this foundational understanding. What is Machine Learning.

Machine Learning 92

Machine Learning Sales Data Science Modeling 92

MLWhiz

MARCH 8, 2019

So I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the different preprocessing techniques that work with Deep learning models and increasing embeddings coverage.

Deep Learning 89

Deep Learning Modeling 89

IBM Big Data Hub

APRIL 22, 2024

For example, we are working on a geospatial foundation model, which can be fine-tuned to track deforestation, detect greenhouse gases (GHGs) or predict crop yields. Foundation models help identify and analyze data, surface trends such as where and why populations are moving and provide insight on how to serve them with renewable energy.

IoT 86

IoT Internet of Things Cost-Benefit Reporting 86

Cloudera

JULY 27, 2021

Fitting Prophet models with complex seasonalities for electricity demand forecasting. The entirely custom front-end to one of our prototype applications with a probabilistic model of NPC real estate. We can build assistive diagnostic interfaces for model building, as in Structural Time Series.

Data Science 111

Data Science Enterprise Experimentation Machine Learning 111

Cloudera

FEBRUARY 25, 2021

AMPs move the starting line for any ML project by enabling data scientists to start with a full end-to-end project developed for a similar use case, including a trained and deployed ML model, as well as prebuilt predictive business applications, out of the box. The work of a machine learning model developer is highly complex.

Deep Learning 81

Deep Learning Machine Learning Forecasting Visualization 81

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications.

Unstructured Data 96

Unstructured Data Cost-Benefit Experimentation Machine Learning 96

MLWhiz

MARCH 29, 2019

So I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the different preprocessing techniques that work with Deep learning models and increasing embeddings coverage.

Deep Learning 79

Deep Learning Modeling 79

Dataiku

SEPTEMBER 18, 2020

There are many libraries out there to help people build deep learning Applications, but one API stands out from the rest when it comes to using state-of-the-art models from the latest architectures with minimal code: Google’s Tensor2Tensor.

Deep Learning 105

Deep Learning Modeling IT 105