O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. that support unsupervised learning. What’s driving this growth?

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

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

Analytics Vidhya

APRIL 15, 2024

Introduction Google AI’s powerhouse language model, Gemini 1.5 Now accessible in over 180 countries via the Gemini API, this update boasts new features designed to empower developers and redefine human-computer interaction. This article digs deep into Gemini 1.5

Interactive 302

Interactive Modeling Analytics IT 302

Analytics Vidhya

JANUARY 26, 2024

Introduction The rise of Large Language Models (LLMs) like ChatGPT has been revolutionary, igniting a new era in how we interact with technology. These sophisticated models, exemplified by ChatGPT, have redefined how we engage with digital platforms.

Interactive 333

Interactive Modeling Technology Analytics 333

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 ]. The first CNN known as LeNet-5 was developed in 1998 by LeCun, et al.

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. The worlds of data science and machine learning move at a much faster pace than data warehousing and much of data engineering.

Data Science 355

Data Science Machine Learning Data Warehouse Deep Learning 355

Analytics Vidhya

DECEMBER 28, 2023

Introduction Temporal graphs are a powerful tool in data science that allows us to analyze and understand the dynamics of relationships and interactions over time. They capture the temporal dependencies between entities and offer a robust framework for modeling and analyzing time-varying relationships.

Data Science 250

Data Science Interactive Modeling Analytics 250

CIO Business Intelligence

JANUARY 26, 2024

Carnegie Mellon University The Machine Learning Department of the School of Computer Science at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning.

Machine Learning 105

Machine Learning Statistics Recreation/Entertainment Data Science 105

Cloudera

JULY 27, 2021

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. We believe the best way to learn what a technology is capable of is to build things with it.

Data Science 115

Data Science Enterprise Experimentation Machine Learning 115

Jen Stirrup

MAY 5, 2020

Apache Spark is what’s known as resilient which means that models can be created and recreated on the fly from a known state. The basis for Apache Spark is what’s known as RDD, Resilient Distributed Data, creating models on the fly and partitioning the data across multiple nodes, and that’s what makes it so popular.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

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

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. 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. Validating Machine Learning Models.

Risk 52

Risk Modeling Metrics Business Objectives 52

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 74

Deep Learning Experimentation Machine Learning Risk 74

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It offers a bootcamp in data science and machine learning for individuals with experience in Python and coding.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

MAY 20, 2022

The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. Carnegie Mellon University.

Machine Learning 145

Machine Learning Statistics Recreation/Entertainment Data Science 145

Smarten

APRIL 19, 2024

OpenAI – Azure OpenAI as the foundational entity for creating GPT models and is based on Large Language Models (LLM). GPT – Is based on a Large Language Model (LLM). Benefits include customized and optimized models, data, parameters and tuning. Open AI was developed by Microsoft.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Analytics Vidhya

DECEMBER 30, 2022

Introduction Natural language processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human (natural) languages.

Analytics 259

Analytics Interactive Modeling IT 259

Laminar Security

DECEMBER 13, 2023

As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult. However, the advent of AI and machine learning (ML) has revolutionized this process.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI As model building become easier, the problem of high-quality data becomes more evident than ever. In this post, we shed some light on various efforts toward generating data for machine learning (ML) models.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

IBM Big Data Hub

FEBRUARY 23, 2024

The emergence of NLG has dramatically improved the quality of automated customer service tools, making interactions more pleasant for users, and reducing reliance on human agents for routine inquiries. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development.

Enterprise 108

Enterprise Interactive Data-driven Key Performance Indicator 108

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. To take one example, AI-facilitated tools like voice navigation promise to upend the way users fundamentally interact with a system.

B2B 49

B2B Interactive Optimization Forecasting 49

Cloudera

FEBRUARY 25, 2021

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. This means that ML development teams can tackle their own ML business use cases more quickly, from those involving churn modeling, to sentiment analysis, to anomaly detection and beyond.

Deep Learning 83

Deep Learning Machine Learning Forecasting Visualization 83

AWS Big Data

MARCH 1, 2023

To facilitate the search, we create features representations (embeddings) for individual columns in the data lake using pre-trained Transformer models from the sentence-transformers library in Amazon SageMaker. A SageMaker Processing job creates embeddings for each column using pre-trained models or custom column embedding models.

Data Lake 83

Data Lake Deep Learning Modeling Interactive 83

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. It is also important to have a strong test and learn culture to encourage rapid experimentation.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. You must detect when the model has become stale, and retrain it as necessary. The Marketing team built the first model, but because it was from marketing, the model optimized for CTR and lead conversion.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

SEPTEMBER 19, 2023

AI personalization utilizes data, customer engagement, deep learning, natural language processing, machine learning, and more to curate highly tailored experiences to end-users and customers.

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

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 95

Unstructured Data Cost-Benefit Experimentation Machine Learning 95

IBM Big Data Hub

OCTOBER 18, 2023

. “Artificial Intelligence Fundamentals” introduces learners to the history of AI and explores the ways that AI makes predictions, understands language and images, and learns using Deep Learning , neural networks that attempt to simulate the human brain.

Machine Learning 83

Machine Learning Deep Learning Technology Marketing 83

IBM Big Data Hub

FEBRUARY 13, 2024

The compact design and touch-based interactivity seemed like a leap into the future. Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Remember how cool it felt when you first held a smartphone in your hand?

Enterprise 128

Enterprise Modeling Testing Data-driven 128

IBM Big Data Hub

JULY 11, 2023

Better machine learning (ML) algorithms, more access to data, cheaper hardware and the availability of 5G have contributed to the increasing application of AI in the healthcare industry, accelerating the pace of change. US, German and French researchers used deep learning on more than 100,000 images to identify skin cancer.

Deep Learning 61

Deep Learning Cost-Benefit Insurance Machine Learning 61

CIO Business Intelligence

JUNE 7, 2022

Those numbers represent the projected growth of chatbot interactions among banking customers between 2019 to 2023 and the cost savings from 862 hours less of work by support personnel, according to research by Juniper Research. In business, when a trend is forecast to grow by more than 3000% and generate cost savings of $7.3

Unstructured Data 97

Unstructured Data Deep Learning Insurance Interactive 97

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We can start with a connecting dataset like LinkedPapersWithCode.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

IBM Big Data Hub

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

Deep Learning 64

Deep Learning Machine Learning Unstructured Data Modeling 64

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Machine Learning | Marketing.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

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

DataRobot

OCTOBER 20, 2021

Individuals interacting with AI systems should possess a baseline data literacy, especially in high-risk use cases that require human collaboration at the final decision-making stage. It is a key component of developing responsible AI, and promotes trust not only in AI concepts but also in individual AI models. What Is Data Literacy?

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52