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Building a Fraud Detection Model with H2O AI Cloud
In a previous article [1], we discussed how machine learning could be harnessed to mitigate fraud. This time, we’ll delve into a step-by-step guide on leveraging H2O AI Cloud to construct efficient fraud detection models. We’ll tackle this process in three critical stages: build, operate, and detect. First, we’ll utilize Driverless AI in ...
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Reducing False Positives in Financial Transactions with AutoML
In an increasingly digital world, combating financial fraud is a high-stakes game. However, the systems we deploy to safeguard ourselves are raising too many false alarms, with over 90% of fraud alerts being false positives. These false positives, not only frustrating for consumers but also costly for financial institutions, can eclipse t...
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Generating LLM Powered Apps using H2O LLM AppStudio – Part1: Sketch2App
sketch2app is an application that let users instantly convert sketches to fully functional AI applications. This blog is Part 1 of the LLM AppStudio Blog Series and introduces sketch2app The H2O.ai team is dedicated to democratizing AI and making it accessible to everyone. One of the focus areas of our team is to simplify the adoption of...
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H2O Managed Cloud With AWS PrivateLink is Now Generally Available
A n essential part of responsibly practicing machine learning is understanding how you secure your data. H2O Managed Cloud offers a single-tenant cloud environment with multiple layers of security – but how do you get your data securely into the cloud for training, and how do you score sensitive information without exposing it to the inte...
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Improving Machine Learning Operations with H2O.ai and Snowflake
Operationalizing models is critical for companies to get a return on their machine learning investments, but deployment is only one part of that operationalization process. With H2O.ai’s latest Snowflake Integration Application, authorized Snowflake users can easily deploy models, significantly reducing deployment timelines and enabling a...
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Improving Manufacturing Quality with H2O.ai and Snowflake
Manufacturers are rapidly expanding their machine learning use cases by leveraging the deep integration between Snowflake’s Data Cloud and the H2O AI Cloud. Many current manufacturing quality checks require that sensor data and image data be processed and analyzed separately. Standard tooling presents challenges in storing and referencin...
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Comprehensive Guide to Image Classification using H2O Hydrogen Torch
In this article, we will learn how to build state-of-the-art models in computer vision and natural language processing within a couple of minutes using H2O Hydrogen Torch. Introduction to H2O Hydrogen Torch H2O Hydrogen Torch (HT) aims to simplify building and deploying deep learning models for a wide range of tasks in computer vision...
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Democratizing Lending through AI
According to the Federal Reserve , nearly 40% of adults in the U.S. sought credit in 2020, only slightly fewer than those who applied in the previous pre-pandemic year; among those who applied more than 1 in 10 were denied credit or were approved for less than they had sought. The reasons behind these denials are many, however, the same r...
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Setting Up Your Local Machine for H2O AI Cloud Wave App Development
This article is for users who would like to build H2O Wave apps and publish them in the App Store within the H2O AI Cloud (HAIC). We will walk through how to set up your local machine for HAIC Wave App development. Instructions Developing with Wave H2O Wave is a framework for building frontends using only python or R. In this article...
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Data Science with H2O.ai: An Introduction to Machine Learning and Predictive Modeling
Our own Jonathan Farland recently recorded a talk about machine learning and predictive modeling. In his talk, Jon also gave an overview of open source H2O and H2O AI Cloud . This video is a great resource for getting up to speed with the latest technology from H2O in half an hour. Some of you may prefer to go through the slides while l...
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Gene Mutation AI
A genomics AI solution from H2O.ai Health Powered by NVIDIA GPUs and NVIDIA AI As precision medicine becomes more widespread, both medical diagnosis and drug discovery are increasingly relying on and leveraging the individual’s genomic and phenotypic profiles. From the multiple types and subtypes of cancer to heart disease, to obesity or ...
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Expression Biomarker AI
A drug discovery AI solution from H2O.ai Health Powered by NVIDIA GPUs and NVIDIA AI In a healthy individual, each cell type has its own metabolic program, carrying out specific functions. This organization is disrupted in disease, either as a cause or a result of it, or both, and this disruption is reflected in the patient’s gene exp...
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Gene Mutation AI and the Future of Cancer Research
A genomics AI solution from H2O.ai Health Powered by NVIDIA GPUs and NVIDIA AI Cancer is a multifactorial disease with exact causes we have only recently begun to understand. While inherited germline mutations are understood to create a genetic predisposition to the disease, stochastic accumulation of somatic mutations over a person’s...
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Vaccine NLP
A population and public health NLP solution from H2O.ai Health Powered by NVIDIA GPUs and NVIDIA AI Social media platforms such as Twitter and Reddit have become invaluable tools for communication between individuals or groups and are widely used globally. As messages on these platforms can instantly be accessed by all users and remain on...
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Tackling Illegal, Unreported, and Unregulated (IUU) Fishing with AI
According to a report by the High-Level Panel for a Sustainable Ocean Economy, it is estimated that illegal, unreported, and unregulated (IUU) fishing accounts for 20 percent of the seafood and up to 50 percent in some areas. These activities not only affect the marine ecosystem but, in a way, are linked to climate change on the planet a...
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Demand Sensing with H2O Wave : Supply Chain Intelligence and Inventory Optimization for Retail, CPG, and FMCG Industries
Demand Sensing can help optimize inventories by analyzing and modeling short-term and real-time signals The supply chains across the Consumer Packaged Goods (CPG), Fast-Moving Consumer Goods (FMCG) and Retail sectors need to continuously monitor the drivers that may impact their internal models and processes. These include systems around ...
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AI Application to Demonstrate K-Means Clustering Using H2O Wave
Note : this is a community blog post by Shamil Dilshan Prematunga . It was first published on Medium . In this blog, I am going to highlight how cool H2O Wave is, by demonstrating my application called “K means App” which was built using Wave 0.20.0 . This is a simple application I have created to demonstrate one of the unsupervised lea...
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A Quick Introduction to PyTorch: Using Deep Learning for Stock Price Prediction
Torch is a scalable and efficient deep learning framework. It offers flexibility and speed to build large scale applications. It also includes a wide range of libraries for developing speech, image, and video-based applications. The basic building block of Torch is called a tensor. All the operations defined in Torch use a tensor. Ok, l...
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Introducing H2O Hydrogen Torch: A No-code Deep Learning Framework
Over and over again we heard from customers, “deep learning is cool, but it’s hard and time consuming.” They kept asking “could someone just make it easier?” In typical “Maker” fashion, you ask, we deliver, H2O Hydrogen Torch . H2O Hydrogen Torch is a new product that enables data scientists and developers to train and deploy state-of-t...
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How to Create Your Spotify EDA App with H2O Wave
In this article, I will show you how to build a Spotify Exploratory Data Analysis (EDA) app using H2O Wave from scratch.H2O Wave is an open-source Python development framework for interactive AI apps. You do not need to know Flask, HTML, CSS, etc. H2O Wave has ready-to-use user-interface components and charts, including dashboard templa...
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H2O.ai releases new H2O MLOps features that improves the explainability, flexibility and configuration of machine learning workflows.
H2O.ai now provides data scientists and machine learning (ML) engineers even more powerful features that give greater control, governance, and scalability within their machine learning workflow – all available on our H2O AI Cloud. Now, H2O MLOps enables you to: Deploy model explanations in production Explainability is core to understa...
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Mission Impossible: Improving Patient Care Through Automated Document Processing
Don’t tell Bob Rogers’ team something can’t be done. When Rogers embarked on an ambitious project to automate the processing of the more than 1.4 million electronically faxed documents received annually by the Center for Digital Health Innovation at the University of California, San Francisco (UCSF CDHI), advisors and vendors initially t...
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What Are Feature Stores and Why Are They Important?
Machine learning (ML) models are only as good as the data fed into them. In tabular problems, the data is a collection of rows (samples) and columns (features). So, you could say that tabular ML models are only as good as the features fed into them. But how do you manage features? Can you share them across the company? Can you easily reu...
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A Beginner’s View of H2O MLOps
Note : this is a community blog post by Shamil Dilshan Prematunga . It was first published on Medium .When we step into the AI application world it is not one easy step. It has a series of tasks that are combined. To convert an idea to the workable stage we must fulfill the requirements in each stage. When we look at existing platforms, t...
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Why Companies Need to Think About MLOps
For years machine learning (ML) researchers have focused on building outstanding models and figuring out how to squeeze every last drop of performance from them. But many have realized that creating top-performing models doesn’t necessarily equate to having them deliver business value. Often the best models can be very complex and costly ...
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An Introduction to Time Series Modeling: Traditional Time Series Models and Their Limitations
In the first article in this series, we broke down the preprocessing and feature engineering techniques needed to build high-performing time series models. But we didn’t discuss the models themselves. In this article, we will dig into this. As a quick refresher, time series data has time on the x-axis and the value you are measuring (dema...
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Announcing the Fully Managed H2O AI Cloud
The H2O AI Cloud is the leading platform to make and access your own AI models and apps. Customers have had access to the H2O AI Hybrid Cloud for the last year, where they could manage the platform themselves on their favorite cloud or on-prem infrastructure. Today, we’re excited to announce a fully managed version of the H2O AI Cloud. Y...
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Amazon Redshift Integration for H2O.ai Model Scoring
We consistently work with our partners on innovative ways to use models in production here at H2O.ai, and we are excited to demonstrate our AWS Redshift integration for model scoring. Amazon Redshift is a very popular data warehouse on AWS. We wanted to expand on the existing capacities of using data from Redshift to train a model on the ...
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Building Resilient Supply Chains with AI
A global pandemic, a fundamental shift in the demand for goods and services worldwide, and the recent blockage of a major international trade route have all highlighted the need to build and maintain resilient supply chains.At the foundation of resilient supply chains lie accurate and reliable forecasts. The majority of traditional softwa...
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Introducing the H2O.ai Wildfire Challenge
We are excited to announce our first AI competition for good – H2O.ai Wildfire Challenge .We’ve structured this challenge to be a global collaborative effort to do good for the world that we share. We want teams to submit their ideas and applications freely, knowing that other teams will learn from what they’ve done to improve their AI ap...
Read moreAnnouncing the H2O AI Feature Store
We’re really excited to announce the H2O AI Feature Store – The only intelligent feature store in the market. We’ve been working on this for many months with our co-development partner: AT&T. This enabled us to build a first-of-its-kind platform that is designed to be enterprise-grade from day 1. It is built with best-of-breed techno...
Read moreNew Features Now Available with the Latest Release of the H2O AI Cloud 21.10
The Makers here at H2O.ai have been busy building new features and enhancing capabilities across our AI platform . Designed to support our core mission of democratizing AI, these additions to our platform simplify the ability to make AI you can trust, operate it efficiently and innovate with ready-made AI applications.Launched in January ...
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Time Series Forecasting Best Practices
Earlier this year, my colleague Vishal Sharma gave a talk about time series forecasting best practices. The talk was well-received so we decided to turn it into a blog post. Below are some of the highlights from his talk. You can also follow the two software demos and try it yourself using our H2O AI Cloud .(Note : The video links with ...
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Improving NLP Model Performance with Context-Aware Feature Extraction
I would like to share with you a simple yet very effective trick to improve feature engineering for text analytics. After reading this article, you will be able to follow the exact steps and try it yourself using our H2O AI Cloud .First of all, let’s have a look at the off-the-shelf natural language processing (NLP) recipes in H2O Driver...
Read moreFeature Transformation with the H2O AI Cloud
It is well known throughout the data science community that data preparation, pre-processing, and feature engineering are one of the most cumbersome parts of the data science workload. So as we continue to innovate here at H2O.ai with our end-to-end automated machine learning (autoML ) capabilities, we challenged ourselves to evolve the...
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Innovation with the H2O AI Cloud
Consumer expectations for responsiveness, personalization, and overall efficiency have risen dramatically over the past several years as technology has become ubiquitous across both our personal and professional lives. These rapidly growing expectations demand an expansion in focus from simply solving narrow use cases with machine learnin...
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AI-Driven Predictive Maintenance with H2O AI Cloud
According to a study conducted by Wall Street Journal , unplanned downtime costs industrial manufacturers an estimated $50 billion annually. Forty-two percent of this unplanned downtime can be attributed to equipment failure alone. These downtimes can cause unnecessary delays and, as a result, affect the business. A better and superior al...
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H2O Integrates with Snowflake Snowpark/Java UDFs: How to better leverage the Snowflake Data Marketplace and deploy In-Database
One of the goals of machine learning is to find unknown predictive features, even hidden from subject matter experts, in datasets that might not be apparent before, and use those 3rd party features to increase the accuracy of the model.A traditional way of doing this was to try and scrape and scour distributed, stagnant data sources on th...
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Regístrese para su prueba gratuita y podrá explorar H2O AI Cloud
Recientemente, lanzamos nuestra prueba gratuita de 14 días de H2O AI Cloud, lo que le brinda la oportunidad de obtener una experiencia práctica con nuestra plataforma más nueva de machine learning. H2O AI Cloud es una plataforma de inteligencia artificial de principio al fin que permite a las organizaciones crear, compartir y usar rápidam...
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H2O.ai logra gran posicionamiento en integridad de visión en el cuadrante Visionarios del Cuadrante Mágico de Gartner 2021 para Data Science y Machine Learning
En H2O.ai, nuestra misión es democratizar la IA y creemos que impulsar el valor de los datos es un esfuerzo de equipo. A menudo, los ingenieros de datos deben organizar y preparar los datos y luego los científicos de datos deben crear modelos. Los modelos, una vez creados, deben ponerse en producción y el personal de TI y de DevOps debe m...
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H2O AI Cloud: Democratizing AI for Every Person and Every Organization
Harnessing AI’s true potential by enabling every employee, customer, and citizen with sophisticated AI technology and easy-to-use AI applications. Democratization is an essential step in the development of AI, and AutoML technologies lie at the heart of it. AutoML tools have played a pivotal role in transforming the way we consume an...
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H2O.ai é a mais avançada por sua capacidade de execução no quadrante dos visionários no relatório do Gartner de Ciências de Dados e Machine Learning em 2021
*Este artigo foi originalmente escrito em inglês pelo SVP de Marketing, Read Maloney, e traduzido para português por Bruna Smith. Na H2O.ai, nossa missão é democratizar a Inteligência Artificial e acreditamos que o valor agregado, gerado a partir dos dados, é um trabalho em equipe. Os dados devem ser organizados e preparados, geralmente ...
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Introducing H2O AI Cloud
Organizations have made large investments in modernizing their data infrastructure and operations, but most still struggle to drive maximum value from their data. Many companies experimented with building large teams of expert data scientists, and while this approach did produce some valuable models, the cost was high and the timeframes ...
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