CIO Business Intelligence

APRIL 17, 2024

Similarly, clothing brand Under Armour recently produced an ad that used AI-generated 3D models of the British boxer Anthony Joshua, based on videos they took of him in the past. Helping software developers write and test code Similarly in tech, companies are currently open about some of their use cases, but protective of others.

Enterprise 129

Enterprise Testing Digital Transformation Software 129

Insight

SEPTEMBER 20, 2019

Segmentation Since a few patients had multiple images in the dataset, the data were separated, by patient, into three parts: training (80%), validation (10%), and testing (10%). The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. The box plot below shows a summary of the testing results.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

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

IBM Big Data Hub

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications. How the models are stored.

Data Science 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

Data Science 101

MAY 20, 2019

Evaluation of Linear Regression Evaluation of Classification Positive/negative skew Poisson regression Fisher’s exact test Pearson PCA Deep learning – high-level, what is is for Neural Networks (RNN vs CNN vs DCN vs GAN). Model Building Model Evalutation SMOTE MICE feature extraction missing data questions AutoML.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

IBM Big Data Hub

JULY 11, 2023

Implementing AI can help recognize unusual or suspicious patterns in insurance claims, such as billing for costly services or procedures not performed, unbundling (which is billing for the individual steps of a procedure as though they were separate procedures), and performing unnecessary tests to take advantage of insurance payments.

Deep Learning 60

Deep Learning Cost-Benefit Insurance Machine Learning 60

Smart Data Collective

FEBRUARY 14, 2021

New SaaS businesses have discovered that data analytics is important for facilitating many aspects of their models. Outline Your Product with Deep Learning Modeling. Deep learning tools can make it easier to model these products. Many design tools have helped with design modeling for years.

Data-driven 86

Data-driven Big Data Deep Learning Software 86

Smart Data Collective

FEBRUARY 20, 2022

With these tools, your SaaS can: Merge and improve the application code constantly Automate the development, testing, and release of software Integrate operations and developer workflows And much more. AWS also offers a variety of AI model development and delivery platforms , as well as packaged AI-based applications.

Cost-Benefit 116

Cost-Benefit Data Lake Software Machine Learning 116

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

Insight

OCTOBER 25, 2019

This category was not considered for the purpose of this project as it does not allow for a 3-way partition for disjoint training, validation, and testing sets. My client also specified that CAD model files of the T-LESS dataset be used for this project, and that one object per class be reserved for testing (Objects 4, 8, 12, 18, 23, 30).

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Insight

APRIL 9, 2019

Machine learning beyond the tech industry Machine learning (ML) has had an incredible impact across industries with numerous applications such as personalized TV recommendations and dynamic price models in your rideshare app. These models are then used to create software that can control the process toward a desired outcome.

Manufacturing 75

Manufacturing Machine Learning Testing Software 75

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

Insight

MAY 7, 2019

Services like Clarifai , and Google AutoML have made it very easy to create image classification models with less labeled data, but it’s not as easy to create such models for text classification. Transfer learning has simplified image classification tasks. fastText, word embedding, and language models?—?in fastText? —?The

Modeling 75

Modeling Testing Machine Learning Interactive 75

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. It is also used for testing more effectively.

Machine Learning 86

Machine Learning Testing Deep Learning Advertising 86

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. The process of creating models is called modeling.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Cloudera

SEPTEMBER 11, 2020

Due to COVID-19, retailers world-wide had their e-commerce capabilities put to the test with entire countries being in lockdown for weeks, even months, due to the pandemic. . What they have learned is that often their legacy Machine Learning models (e.g. Data and analytics.

Manufacturing 92

Manufacturing Forecasting Digital Transformation Sales 92

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. Transfer learning is basically like cheap cable tv for a resource-constrained network.

Metrics 58

Metrics Optimization Modeling Testing 58

Smarten

APRIL 19, 2024

The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. OpenAI – Azure OpenAI as the foundational entity for creating GPT models and is based on Large Language Models (LLM). in next several years.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Cloudera

SEPTEMBER 12, 2018

AbbVie’s platform uses analytics and machine learning, including natural language processing, deep learning, and unsupervised learning, to proactively identify issues and opportunities. Bob Gourley , Founder Crucial Point LLC and Publisher, CTOvision.com, ThreadBrief.com, @BobGourley. Cloud Success: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. As the story goes, the general history of DG is punctuated by four eras: “Application Era” (1960–1990) – some data modeling, ?though Newer work in machine learning (e.g.,

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

APRIL 27, 2023

To accomplish this, OpenAI has employed Ray to power the distributed compute platform to train each release of the GPT models. In the blog we will cover how Ray can be used in Cloudera Machine Learning’s open-by-design architecture to bring fast distributed AI compute to CDP. With that in place, we can now spin up a Ray cluster.

Machine Learning 79

Machine Learning Dashboards Deep Learning Testing 79

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

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 119

Deep Learning Machine Learning Data Science Cost-Benefit 119

DataRobot Blog

MARCH 9, 2022

This article was originally published at Algorithimia’s website. 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. The company was acquired by DataRobot in 2021. Find out more about DataRobot MLOps here.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

Domino Data Lab

JULY 15, 2021

These data science tools are used for doing such things as accessing, cleaning and transforming data, exploratory analysis, creating models, monitoring models and embedding them in external systems. IDEs (also sometimes referred to as notebooks) is a coding tool that makes it easier to develop and test code.

Data Science 145

Data Science Visualization Modeling Enterprise 145

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. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. More use-cases are being tried, tested and built everyday, the innovation in this field will not cease for the next few years. Applications of AI.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 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). specifically convolutional neural networks (CNN)?—?can

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Insight

FEBRUARY 13, 2019

In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing. This allows BERT to provide significantly higher performance than models that are only able to leverage a small task-specific dataset. Download the BERT model files. Column 3 : A column of all the same letter?—?this

Testing 72

Testing Machine Learning Deep Learning Modeling 72

DataRobot

NOVEMBER 9, 2021

“One look is worth a Thousand Words” This phrase was used in 1913 to convey that graphics had a place in newspaper publishing. There are some interesting insights in adding unstructured features to the models. For adding image based features on the models, we use the Pyts library, which provides functions to generate GAF matrices.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

Domino Data Lab

MARCH 3, 2019

We had big surprises at several turns and have subsequently published a series of reports. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). The first survey started as a simple exploration into mainstream adoption of machine learning (ML).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Data Science and Beyond

OCTOBER 15, 2017

The hardest parts of data science are problem definition and solution measurement, not model fitting and data cleaning , because counting things is hard. I’ve also dabbled in deep learning , marine surveys , causality , and other things that I haven’t had the chance to write about. Thanks, that’s helpful.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

Domino Data Lab

MARCH 29, 2021

Maintaining the cluster and the underlying infrastructure configuration can be a complex and time-consuming task Lack of GPU acceleration – Complex machine workloads, especially the ones involving Deep Learning, benefit from GPU architectures that are well adapted for vector and matrix operations. GPU) and use bitnami/spark:2.4.6

Cost-Benefit 98

Cost-Benefit Machine Learning Testing Interactive 98

Domino Data Lab

JULY 9, 2019

Assessing whether a business stakeholder is trying to solve for a problem that is descriptive, predictive, or prescriptive and then re-framing the problem as supervised learning, unsupervised learning, or reinforcement learning, respectively. One of the ways I frame that is, “Are you looking to build a predictive model?

Data Science 112

Data Science Machine Learning Advertising Modeling 112

CIO Business Intelligence

APRIL 27, 2022

Data fabric, data cleansing and tagging, data models, containers, inference at the edge – cloud-enabled platforms are all “go-to” conversation points. This is especially true for those companies that have experienced the impact of the global pandemic, and how that stress-tested their existing business model.

Strategy 143

Strategy Data-driven Internet of Things Measurement 143

O'Reilly on Data

JANUARY 25, 2021

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. Models are neither code nor data, and we don’t have adequate tools for versioning models either (though tools like MLflow are a start).

Machine Learning 363

Machine Learning Software Testing Technology 363