O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. In this article, we turn our attention to the process itself: how do you bring a product to market? Identifying the problem.

Marketing 362

Marketing Experimentation Metrics Testing 362

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 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

O'Reilly on Data

MARCH 7, 2019

Language understanding benefits from every part of the fast-improving ABC of software: AI (freely available deep learning libraries like PyText and language models like BERT ), big data (Hadoop, Spark, and Spark NLP ), and cloud (GPU's on demand and NLP-as-a-service from all the major cloud providers). Azure Text Analytics.

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

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 127

Enterprise Modeling Testing Data-driven 127

Andrew White

JANUARY 5, 2023

In fact, in the WSJ just before Christmas, there was an article titled, “ ChatGPT Wrote My AP Essay – and I got a Passing Grade ”. The article explains how the author asked ChatGPT to write a 500-word essay on The Great Gatsby. This is what deep learning does and it does it far better than we can given the volume of data.

Deep Learning 64

Deep Learning Testing Modeling IT 64

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. TensorFlow runs on both CPUs and GPUs. Tensorflow 2.0,

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

CIO Business Intelligence

JUNE 1, 2022

These supercomputers power exciting innovations in deep learning, disease control, and physics—think bionic eyes, DNA sequencing for infectious disease research, and the study of time crystals. . CSIRO’s Bracewell Delivers Deep Learning, Bionic Vision. Bracewell’s IO500 score was 99.64, IO500 BW 39.90

Deep Learning 105

Deep Learning Snapshot Optimization Data Quality 105

CIO Business Intelligence

MARCH 18, 2024

By the time information slogged through every layer of our hierarchical operating model, all comparative advantages were lost. The enemy’s model, however, amplified the power of their bargain-bin tech. I believe large language models (LLMs) will prompt most organizations to face the same reckoning.

Broadcasting 73

Broadcasting Deep Learning Risk Strategy 73

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

CIO Business Intelligence

APRIL 24, 2023

Generative AI (Artificial Intelligence) and its underlying foundation models represent a paradigm shift in innovation, significantly impacting enterprises exploring AI applications. These foundation models are trained on vast amounts of data. The model can then predict or classify new, previously unseen data.

Enterprise 52

Enterprise Deep Learning Modeling Machine Learning 52

Domino Data Lab

DECEMBER 1, 2019

This article covers how to detect data drift for models that ingest image data as their input in order to prevent their silent degradation in production. Introduction: preventing silent model degradation in production. Model monitoring: the approach. Run the example in a complementary Domino project.

Modeling 77

Modeling Machine Learning Deep Learning Testing 77

Domino Data Lab

JULY 28, 2021

In this article, we will provide an overview of the three overlapping components of data science, the importance of communication and collaboration, and how the Domino Data Lab MLOps platform can help improve the speed and efficiency of your team. All models are not made equal. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Smarten

JUNE 14, 2023

In this article, we will discuss GPT, its roots and its limitations, in order to provide insight into where this technology is today and how it can be used now to inform and support apps, software products and technology services. GPT, or Generative Pre-Trained Transformer, is a Large Language Model (LLM).

Optimization 52

Optimization IT Digital Transformation Consulting 52

Smart Data Collective

FEBRUARY 20, 2022

In this article we will list 10 things AWS can do for your SaaS company. This article finally gets to the core question we started with: what can AWS do for your SaaS business? AWS also offers a variety of AI model development and delivery platforms , as well as packaged AI-based applications. Let’s just dive right in.

Cost-Benefit 116

Cost-Benefit Data Lake Software Machine Learning 116

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). Training domain-specific models.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 63

Deep Learning Machine Learning Unstructured Data Modeling 63

Grooper

JUNE 22, 2021

This is how machine learning works. This is the reality of deep learning, or convoluted neural networks. In the case of machine learning, very specific outcomes are achievable. Machine learning (AI) learns when a new input is fed into the algorithm to change the way it works. Mystery Black Boxes.

Deep Learning 57

Deep Learning Machine Learning Software Testing 57

Domino Data Lab

JULY 28, 2021

In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. In its current form , data science is limitless in terms of industry and application; the only requirement is data, compute power, data scientists, and a desire to become model-driven.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

CDW Research Hub

JULY 31, 2019

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

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.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Insight

MAY 16, 2019

It is a high-level, multifaceted field that allows machines to iteratively learn and understand complex representations from images and videos to automate human visual tasks. How Deep Learning scales based on the amount of Data [Copyright: Andrew Ng ]. Transfer Learning?—?YOLO. Precision?—?Recall

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

Smart Data Collective

JULY 30, 2020

In December, Springer published an insightful article about the value of deep learning for VPNs. The article “Deep learning-based real-time VPN encrypted traffic identification methods” delves into the use of machine learning to improve encryption models. What is VPN.

Machine Learning 86

Machine Learning Testing Deep Learning Advertising 86

O'Reilly on Data

OCTOBER 19, 2021

This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. Not only is data larger, but models—deep learning models in particular—are much larger than before. However, the concept is quite abstract.

IT 346

IT Testing Experimentation Software 346

Insight

JANUARY 14, 2020

a “pre-trained” model) to be recycled and reused for many different tasks. 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. A vanilla NN can only detect features that are in identical positions within the image.

Metrics 58

Metrics Optimization Modeling Testing 58

Domino Data Lab

APRIL 3, 2019

This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. Welcome back to our monthly burst of themes and conferences.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more. If we had AGI, how would we know it?

Modeling 363

Modeling Interactive Optimization Deep Learning 363

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage. GPT – Is based on a Large Language Model (LLM).

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

DataRobot Blog

FEBRUARY 2, 2023

Large language models, also known as foundation models, have gained significant traction in the field of machine learning. These models are pre-trained on large datasets, which allows them to perform well on a variety of tasks without requiring as much training data. What Are Large Language Models?

Modeling 52

Modeling Machine Learning Data Processing Interactive 52

CIO Business Intelligence

APRIL 15, 2022

MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. For example, Driggs’ group found that their own model was flawed because it was trained on a data set that included scans of patients that were lying down while scanned and patients that were standing up.

Analytics 145

Analytics Machine Learning Insurance Testing 145

IBM Big Data Hub

JANUARY 10, 2024

In this article, we’ll discuss how AI technology functions and lay out the advantages and disadvantages of artificial intelligence as they compare to traditional computing methods. For optimal performance, AI models should receive data from a diverse datasets (e.g., What is artificial intelligence and how does it work?

Unstructured Data 84

Unstructured Data Deep Learning Cost-Benefit Modeling 84

Sisense

MAY 26, 2020

For more details, refer to this article. While training a model for NLP, words not present in the training data commonly appear in the test data. Because of this, predictions made using test data may not be correct. Test data then contains this sentence: Pasta is delicious. For more details, check out this article.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

DataRobot Blog

MARCH 9, 2022

This article was originally published at Algorithimia’s website. This article may not be entirely up-to-date or refer to products and offerings no longer in existence. With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

Sisense

AUGUST 6, 2020

In this article, we’ll dig into the ways AI can help you accomplish these goals, allowing you and your team to envision the future of your product or service. Be sure test cases represent the diversity of app users. When building your data model, it’s vital to avoid both underfitting and overfitting. The perfect fit.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. deep learning) there is no guaranteed explainability. This is to prevent any information leakage into our test set.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

BizAcuity

MARCH 31, 2022

There have been so many articles published about AI and its applications, you can find millions of articles from broad concepts to deep technical literature on the internet. This article (like thousands of other articles), is aimed at presenting consolidated information about AI for business in simple language.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105