DataRobot Blog

JULY 27, 2022

However, machine learning utilization is often unpredictable, which makes scaling sometimes a huge challenge. You interact with everything via our Python clients wrapping our API endpoints. Investing in AI/ML is no longer an option but is critical for organizations to remain competitive. Data Science Expertise Meets Scalability.

Metrics 52

Metrics Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 81

Machine Learning Modeling Deep Learning Predictive Modeling 81

Domino Data Lab

JULY 28, 2021

Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions. 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. None of these techniques are new.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. But for most enterprise, using machine learning…not really.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

AWS Big Data

JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. Jupyter notebooks are web-based interactive platforms. In the Choose tuning options section, you can tune performance and cost metrics available for the ML transform. Review the details in the Estimate quality metrics section and choose Close.

Insurance 83

Insurance Visualization Data Lake Metrics 83

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

Smarten

APRIL 19, 2024

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

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

AUGUST 10, 2021

At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Sisense

AUGUST 6, 2020

AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. So what are the high-level steps to incorporate AI and machine learning into new and existing products? An obvious mechanical answer is: use relevance as a metric. The future will be intelligent.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

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

DataRobot Blog

FEBRUARY 2, 2023

Large language models, also known as foundation models, have gained significant traction in the field of machine learning. Learn how you can easily deploy a pre-trained foundation model using the DataRobot MLOps capabilities, then put the model into production. What Are Large Language Models?

Modeling 52

Modeling Machine Learning Data Processing Interactive 52

Domino Data Lab

MAY 8, 2019

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. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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

DataRobot Blog

DECEMBER 20, 2022

DataRobot combines these datasets and data types into one training dataset used to build machine learning models. By using this model, all accuracy metrics would also comply with national valuation regulations —as defined by the Bank of Spain. Consume Results with DataRobot AI Applications.

Management 59

Management Machine Learning Optimization Modeling 59

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is now able to automatically create and maintain materialized views and then transparently rewrite queries to use the materialized views using the machine-learned automated materialized view autonomics feature in Amazon Redshift. Aamer Shah is a Senior Engineer in the Amazon Redshift Service team.

Data Warehouse 101

Data Warehouse Cost-Benefit Dashboards Optimization 101

Insight

NOVEMBER 5, 2019

Can we ever hope to appreciate the interactions between hundreds or thousands of factors that shape outcomes for a single patient? A Multimodal Deep Learning Model A flexible, multimodal architecture for predicting diagnoses or survival from ICU data. What if their interplay is not merely additive? Thanks for reading!

Deep Learning 61

Deep Learning Modeling Insurance Metrics 61

Insight

MARCH 28, 2019

Like Derek, the first step Yanxia took was to classify each review’s sentences into topic categories, but she opted to use a machine learning-based approach to identify 14 latent topics. Yanxia then used a combination of quantitative and qualitative metrics to interpret each topic group identified by LDA.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

Business Over Broadway

DECEMBER 20, 2018

The importance of data science and machine learning continues to grow in business and beyond. Favorite Data Science and Machine Learning Blogs, Podcasts and Newsletters – In a worldwide survey, over 16,000 data professionals were asked to indicate their favorite data science blogs, podcasts and newsletters.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

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

O'Reilly on Data

JANUARY 25, 2021

We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. AI, Machine Learning, and Data. Artificial intelligence, machine learning, and data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. Here’s an interactive visualization for understanding texts: scattertext , a product of the genius of Jason Kessler. Usually it’s human-generated text, but not always. for a, b in pairs:?.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110