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75 results Category: Year:H2O Release 3.28 (Yu)
There’s a new major release of H2O, and it’s packed with new features and fixes! Among the big new features in this release, we’ve introduced support for Hierarchical GLM, added an option to parallelize Grid Search, upgraded XGBoost with newly added features, and improved our AutoML framework. The release is named after Bin Yu .Hierarchi...
Read moreWhy you should care about debugging machine learning models
This blog post was originally published here. Authors: Patrick Hall and Andrew Burt For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing p...
Read moreInterview with Arno Candel | AutoML | Physics | CTDS.Show
In this episode, Sanyam Bhutani interviews Dr. Arno Candel: CTO at H2O.ai They talk about Arno’s journey into the field with amazing comments and insights by Arno applicable to the field. They talk all about Arno’s journey and ML, Automated Machine Learning Broadly speaking. Arno’s journey from Physics to Software Engineering to Machine L...
Read moreHow to Effectively Employ an AI Strategy in your Business
Artificial Intelligence has evolved from being a buzz word to a reality today. Companies with expertise in machine learning systems are looking to graduate to Artificial Intelligence-based technologies. The enterprises that do not yet have a machine learning culture are trying to devise a strategy to put one in place. Amidst t...
Read moreScalable AutoML in H2O
Note: I’m grateful to Dr. Erin LeDell for the suggestions, corrections with the writeup. All of the images used here are from the talks’ slides. Erin Ledell’s talk was aimed at AutoML : Automated Machine Learning , broadly speaking, followed by an overview of H2O’s Open Source Project and the library. H2O AutoML provides an easy-to-use ...
Read moreMeet Yauhen Babakhin: The first and the only Kaggle Grandmaster from Belarus
There is more to competitive Data Science than simply applying algorithms to get the best possible model. The main takeaway from participating in these competitions is that they provide an excellent opportunity for learning and skill-building. The learnings can then be utilized in one’s academic or professional life. Kaggle is one of th...
Read moreClimbing the AI and ML Maturity Model Curve
AI/ML Maturity Model Curve/StepsAI/ML Maturity models are published and updated periodically by a lot of vendors. The end goal is almost always about effecting transformation and automate processes in a short period and making AI the DNA/core of the business.One of the biggest challenges for businesses today is to clearly define what succ...
Read moreHow to write a Transformer Recipe for Driverless AI
What is a transformer recipe? A transformer (or feature) recipe is a collection of programmatic steps, the same steps that a data scientist would write a code to build a column transformation. The recipe makes it possible to engineer the transformer in training and in production. The transformer recipe, and recipes, in general, provide a...
Read moreNovel Ways To Use Driverless AI
I am biased when I write that Driverless AI is amazing, but what’s more amazing is how I see customers using it. As a Sales Engineer, my job has been to help our customers and prospects use our flagship product. In return, they give us valuable feedback and talk about how they used it. Feedback is gold to us. Driverless AI has evolved in...
Read moreImage Tasks on H2O Driverless AI
I’d like to thank Grandmaster Yauhen Babakhin for reviewing the drafts and the very useful corrections & suggestions. Link to the video. IntroductionIn this talk Kaggle GrandMaster and Data Scientist at H2O.ai: Yauhen Babakhin shows us a few prototype demos of how DriverlessAI’s upcoming release will work with Image Data and the relat...
Read moreAccelerate Machine Learning workflows with H2O.ai Driverless AI on Red Hat OpenShift, Enterprise Kubernetes Platform
Organizations globally are operationalizing containers and Kubernetes to accelerate Machine Learning lifecycles as these technologies provide data scientists and software developers with much needed agility, flexibility, portability, and scalability to train, test, and deploy ML models in production. Red Hat OpenShift is the industry’s mo...
Read moreImporting, Inspecting, and Scoring With MOJO Models Inside H2O
Machine-learning models created with H2O may be exported in two basic ways: Binary format, Model Object, Optimized (MOJO). An H2 O model can be saved in a binary format, which is tied to the very specific version of H2 O it has been created with. There are multiple reasons for such a restriction. One of the important reasons is that...
Read moreNatural Language Processing in H2O’s Driverless AI
Note: I’d like to thank Grandmaster SRK for a lot of suggestions and corrections with the writeup.Note: All images used here are from the talk. Link to the slides Link to the video Note 2: All of the discussion here is related to NLP. DriverlessAI also supports other domains that are covered in other talks and posts (releasing soon). Driv...
Read moreHighlights of H2O World New York 2019
H2O World New York happened a few days ago and we are still in awe of the conference. It is rewarding to see such a strong community and recognized industry professionals making meaningful connections and learning with each other. We are grateful for having so many makers and customers joining us – in person and via live stream – for a fu...
Read moreTakeaways from the World’s largest Kaggle Grandmaster Panel
Disclaimer: We were made aware by Kaggle of adversarial actions by one of the members of this panel. This panelist is no longer a Kaggle Grandmaster and no longer affiliated with H2O.ai as of January 10th, 2020. Personally, I’m a firm believer and fan of Kaggle and definitely look at it as the home of Data Science. ...
Read moreA Full-Time ML Role, 1 Million Blog Views, 10k Podcast Downloads: A Community Taught ML Engineer
Content originally posted in HackerNoon and Towards Data Science 15th of October, 2019 marks a special milestone, actually quite a few milestones. So I considered sharing it in the form a blog post, on a publication that has been home to all of my posts The online community has been too kind to me and these blog posts have been a method ...
Read moreThe Data Scientist who rules the "Data Science for Good" competitions on Kaggle
In conversation with Shivam Bansal: A Data Scientist, a Kaggle Kernel’s Grandmaster, and three times winner of Kaggle’s Data Science for Good Competition. Communication is an art and a useful tool in the Data Science domain. Being able to communicate the insights is necessary so that others can take the required actions based on the resu...
Read moreA Deep Dive into H2O’s AutoML
The demand for machine learning systems has soared over the past few years. This is majorly due to the success of Machine Learning techniques in a wide range of applications. AutoML is fundamentally changing the face of ML-based solutions today by enabling people from diverse backgrounds to use machine learning models to address complex ...
Read moreMake your own AI — Add Your Game to Auto-ML Models
When Features and Algorithms compete, your Business Use Case(s) wins! H2O Driverless AI is an Automatic Feature Engineering /Machine Learning platform to build AI/ML models on tabular data. Driverless AI can build supervised learning models for Time Series forecasts, Regression , Classification , etc. It supports a myriad of built-i...
Read moreH2O World New York: The Countdown is On!
Every H2O World is magical. The preparation for the conference starts many months in advance and we put a lot of effort and love in every single detail to provide our beloved community with the best experience possible. Our upcoming H2O World New York on October 22 is the third edition I work on as part of the marketing team at H2O.ai. My...
Read more5 Key Takeaways On Overcoming Gender and Diversity Barriers
Overcoming gender and diversity barriers in the workplace is a challenge for many industries. Therefore, listening to women and discussing the topic is the first step towards finding out how to address gender bias and possible inequalities. Last month, H2O.ai organized a panel in New York: Breaking gender and diversity barriers in machi...
Read morePredicting Failures from Sensor Data using AI/ML — Part 2
This is Part 2 of the blog post series and continuation of the original post, Predicting Failures from Sensor Data using AI/ML — Part 1 .Missing Values & Data ImbalanceOne of the things to note is that the hard-disk data set has a lot of missing values across its columns. Check out the Missing Data Heat Map on the training data set — ...
Read moreH2O Driverless AI: The Workbench for Data Science
This blog was written by Rohan Gupta and originally published here. 1. IntroductionIn today’s world, being a Data Scientist is not limited to those without technical knowledge. While it is recommended and sometimes important to know a little bit of code, you can get by with just intuitive knowledge. Especially if you’re on H2O’s Driverle...
Read moreH2O Driverless AI Acceleration with Intel DAAL
This week at Strata NY 2019 we will be demoing a custom recipe that incorporates the Intel Data Analytics Acceleration Libraray (DAAL) algorithm into Driverless AI. This blog will provide an introduction to Intel DAAL and how the Make-Your-Own-Recipe capability extends H2O Driverless AI. If you are at Strata NY 2019, stop by the Intel bo...
Read moreCustom recipes for Driverless AI: Prophet and pmdarima cases
Last updated: 09/23/19 H2O Driverless AI provides a great new feature called “custom recipes”. These recipes are essentially custom snippets of code which can incorporate any machine learning algorithm , any scorer/metric and any feature transformer. A user can create custom recipes using python utilizing any external library or his/her o...
Read moreFrom Academia to Kaggle and H2O.ai: How a Physicist found love in Data Science
Learning and taking inspirations from others is always helpful. It makes even more sense in the Data Science realm, which is continuously being bombarded with new courses, MOOCs, and recommendations with every passing day. Not only such a lot of choices become overwhelming but also perplexing at times. With this thought in mind, we bring...
Read moreRegression Metrics' Guide
Introduction As part of my role within the automated machine learning space with H2O.AI and Driverless AI, I have seen that many times people struggle to find the right optimization metric for their data science problems. This process is even more challenging in regression problems where the errors are often not bounded like you norma...
Read moreSeries ‘D’emocratize
Last month was very emotional for me and I suspect it was the same for many of my fellow Makers at H2O.ai. The news broke that H2O.ai raised its Series D funding of $72.5 million led by Goldman Sachs and Ping An. While some of my friends were ecstatic for me, I felt like a big weight had been lifted off me. The best word to describe what ...
Read moreDriverless AI can help you choose what you consume next
Last updated: 09/06/19 Steve Jobs once said, “A lot of times, people don’t know what they want until you show it to them’. This makes sense, especially in this era of constant choice overload. Consumers today have access to a plethora of products just at the click of their mouse. These innumerable choices can sometimes turn out to be ...
Read moreStartup Aims to Democratize AI
Adam Janofsky at the Wall Street Journal wrote a wonderful article about our company, and our eloquent and philosophical CEO and Founder, Sri Ambati. The makers at H2O.ai believe deeply in our mission to democratize AI for everyone, and we can see a future where every company can be an AI company. Read more below, and enjoy! Startup Aims ...
Read morePredicting Failures from Sensor Data using AI/ML— Part 1
Last updated: 08/26/19 Whether it’s healthcare, manufacturing or anything that we depend on either personal or in business, Prevention of a problem is always known to be better than cure! Classic prevention techniques involve time-based checks to see how things are progressing, positively or negatively. Time-based chec...
Read moreNew Innovations in Driverless AI
What’s new in Driverless AIWe’re super excited to announce the latest release of H2O Driverless AI . This is a major release with a ton of new features and functionality. Let’s quickly dig into all of that: Make Your Own AI with Recipes for Every Use Case: In the last year, Driverless AI introduced time-series and NLP recipes to meet the...
Read moreInterns Gonna Make
Blog post by Megan Chan When I first walked through the front doors of the H2O.ai Mountain View office, I have to admit, thoughts of robots, cyborgs, and Arnold Schwarzenegger as The Terminator were in the back of my mind. However, my initial preconceived notions were quickly put to rest.I am a third-year college intern studying Psycholog...
Read moreA Maker Data Scientist’s journey: from Sudoku to Kaggle
If you put enough smart people together in one space, good things happen. Erik Hersman One of the perks of being a part of H2O.ai is that you get to work with some of the brightest minds on the planet. Here you get to closely engage with people who have a great deal of experience, as well as expertise. One such set of specialists here ar...
Read moreMy Summer Internship at H2O.ai
I can’t believe the summer is nearing an end. What an amazing experience I have had at H2O.ai. As I reflect back, I am so fortunate to have learned so much, formed meaningful relationships, developed people skills and applied my creativity. The whole team has been so encouraging, supportive, and inviting throughout my internship, makin...
Read moreDetecting Sarcasm is difficult, but AI may have an answer
Recently, while shopping for a laptop bag, I stumbled upon a pretty amusing customer review: “This is the best laptop bag ever. It is so good that within two months of use, it is worthy of being used as a grocery bag.” The innate sarcasm in the review is evident as the user isn’t happy with the quality of the bag. However, as the sentence...
Read moreMitigating Bias in AI/ML Models with Disparate Impact Analysis
Everyone understands that the biggest plus of using AI/ML models is a better automation of day-to-day business decisions, personalized customer service, enhanced user experience, waste elimination, better ROI, etc. The common question that comes up often though is — How can we be sure that the AI/ML decisions are free from bias/discrimina...
Read moreH2O Release 3.26 (Yau)
There’s a new major release of H2O, and it’s packed with new features and fixes! Among the big new features in this release, we’ve introduced the ability to define a Custom Loss Function in our GBM implementation, and we’ve extended the portfolio of our machine learning algorithms with the implementation of the SVM algorithm. The release...
Read moreA Driverless Approach to Make Forecasting Easy — Part 1
You are from the supply chain department or in a role in charge of creating future estimates on Product Sales, Patient admission, Retail Store Staffing, Energy use, Ticket sales, etc., based on historical data. A common problem is to forecast numbers one week, 4 weeks, 6 months or 1–5 year, etc., in future — basically short term &a...
Read moreCustom Machine Learning Recipes: The ingredients for success
Last updated: 07/23/19Machine learning is akin to cooking in several ways. A perfect dish originates from a tried-and-tested recipe, has the right combination of ingredients, and is baked at just the right temperature. Successful AI solutions work on the same principle. One needs fresh and right quality ingredients in the form of data, ...
Read moreAI for Smarter Manufacturing
Code 3Manufacturing is a centuries old industry and has seen significant changes dating back to the first Industrial Revolution in the late 18th century. The use of conveyor belt assembly lines to replace assembly workers, newer precision robot technologies to further reduce manufacturing time, advances in ERP, historian databases, stora...
Read moreLeads to Leases
There is such a large amount of unstructured data being produced by companies. I personally find it so interesting that there is so much meaning and hidden value in text, audio, and visual content. Until recently, much of this data would go unused. However, since the rise of machine learning and artificial intelligence, it became possibl...
Read moreGetting started with H2O using Flow
This blog was originally published on towardsdatascience: https://towardsdatascience.com/getting-started-with-h2o-using-flow-b560b5d969b8A look into H2O’s open-source UI for combining code execution, text, plots, and rich media in a single document. Data collection is easy. Decision making is hard. Today, we have access to a humungous...
Read moreArmadaHealth Uses AI to Match Patients with Specialists to Improve Health Outcomes
As an intern for H2O.ai, I am amazed to see how instrumental AI has been in transforming people’s lives for the better. Especially in healthcare, AI is bringing increased efficiency, ease, and helping people lead healthier lives. In this blog, I learned about how AI is helping potential patients find the right specialist for their needs a...
Read moreToward AutoML for Regulated Industry with H2O Driverless AI
Predictive models in financial services must comply with a complex regime of regulations including the Equal Credit Opportunity Act (ECOA), the Fair Credit Reporting Act (FCRA), and the Federal Reserve’s S.R. 11-7 Guidance on Model Risk Management. Among many other requirements, these and other applicable regulations stipulate predictive ...
Read moreUnderwrite.ai Transforms Credit Risk Decision-Making Using AI
Determining credit has been done by traditional techniques for decades. The challenge with traditional credit underwriting is that it doesn’t take into account all of the various aspects or features of an individual’s credit ability. Underwrite.ai, a new credit startup, saw this as an opportunity to apply machine learning and AI to impro...
Read moreThe Reproductive Science Center of SF Bay Area uses AI to Treat Infertility
Having your own baby may be a dream that many people have but some cannot realize until they seek specialized help. The Reproductive Science Center of SF Bay Area is one of the pioneer organizations conducting in-vitro fertilization. They strive to produce healthy babies for their patients. However, every patient has their own set of obst...
Read moreMachine Learning on VMware: Training a Model with H2O.ai Tools, Inference using a REST Server and Kubernetes
This blog was originally posted by Justin Murray of VMware and can be accessed here. In this article, we explore the tools and process for (1) training a machine learning model on a given dataset using the H2O Driverless AI (DAI) tool, and (2) deploying a trained model, as part of a scoring pipeline, to a REST server for use by busi...
Read moreAn Overview of Python’s Datatable package
This blog originally appeared on Towardsdatascience.com “There were 5 Exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days”: Eric Schmidt If you are an R user, chances are that you have already been using the data.ta...
Read moreBuilding an Interpretable & Deployable Propensity AI/ML Model in 7 Steps…
To start with, you may have a tabular data set with a combination of: Dates/Timestamps Categorical Values Text strings Numeric Values A business sponsor wants to build a Propensity to Buy model from historical data.How many Steps does it take? Let’s find out. We are going to use H2O’s Driverless AI instance with 1 GPU (optional...
Read moreForrester Research recognizes H2O.ai as a leader in the New Automatic Machine Learning Wave
Today, The Forrester New Wave™ : Automation-Focused Machine Learning Solutions, Q2 2019 was published by Forrester Research. We are thrilled that this leading analyst firm recognized us as a clear leader in their Automatic Machine Learning evaluation. We could not be prouder of our unwavering strategy and hard work that we believe is prop...
Read moreH2O.ai Automatic Machine Learning on Red Hat OpenShift Container Platform Delivers Data Science Ease and Flexibility at Scale
Last week at Red Hat Summit in Boston, Sri Ambati, CEO and Founder, demonstrated how to use our award-winning automatic machine learning platform, H2O Driverless AI , on Red Hat OpenShift Container Platform. You can watch the replay here .What we showed not only helps data scientists achieve results, it also enables them to scale their ...
Read more6 Tips to Having it All
I posted this blog on Medium two years ago, thought I’d share a slight rework of it with all the Mothers and Makers out there again.It’s Mother’s Day, and today is when I count my blessings. I am the mother of a wonderful blended family. I have four children of my own, and three stepchildren. Do the math… that’s 7! They are all great you...
Read moreAI/ML Projects — Don’t get stymied in the last mile
Data Scientists build AI/ML models from data, and then deploy it to production – in addition to a plethora of tasks around data insights, data cleansing etc., Part of the Data Scientist job description/requirement is making models available for transparency, auditability as well as explainability for both regulators as well as internal bu...
Read moreHortifrut uses AI to Determine the Freshness of Blueberries
Who doesn’t love sweet, delicious blueberries?Providing a steady supply of beautiful, tasty berries to the market is no small effort and Hortifrut, based in Chile, has been growing and distributing berries for the last 30 years. Today, they are using AI to provide fresh berries to the world everyday.Hortifrut, the largest global producer ...
Read moreCan Your Machine Learning Model Be Hacked?!
I recently published a longer piece on security vulnerabilities and potential defenses for machine learning models. Here’s a synopsis.IntroductionToday it seems like there are about five major varieties of attacks against machine learning (ML) models and some general concerns and solutions of which to be aware. I’ll address them one-by-o...
Read moreH2O Driverless AI Updates
We are excited to announce the new release of H2O Driverless AI with lots of improved features.Below are some of the exciting new features we have added:Version 1.6.1 LTS (April 18, 2019) – Available here Several improvements for MLI (partial dependence plots, Shapley values) Improved documentation for model deployment, time-series ...
Read moreH2O World Explainable Machine Learning Discussions Recap
Earlier this year, in the lead up to and during H2O World, I was lucky enough to moderate discussions around applications of explainable machine learning (ML) with industry-leading practitioners and thinkers. This post contains links to these discussions, written answers and pertinent resources for some of the most common questions asked ...
Read moreH2O-3, Sparkling Water and Enterprise Steam Updates
We are excited to announce the new release of H2O Core, Sparkling Water and Enterprise Steam.Below are some of the new features we have added:H2O-3 Yates (3.24.0.1) – 3/31/2019Download at: http://h2o-release.s3.amazonaws.com/h2o/rel-yates/1/index.html Bug [PUBDEV-6159] – The AutoMLTest.java test suite now runs correctly on a local mach...
Read moreH2O Release 3.24 (Yates)
There’s a new major release of H2O, and it’s packed with new features and fixes! Among the big new features in this release, we’ve introduced cross-version support for model import, added new features for model interpretation, provided much-improved support for reading data from Apache Hive, and included various algorithm and AutoML impr...
Read moreBuilding AI/ML models on Lending Club Data, with H2O.ai — Part 1
Lending Club publishes its basic loan databases to the public and a full version to its customers — anonymized of course. You can find the download page from this link (screenshot below): The publicly downloadable loan data has various attributes — roughly 150+ columns that have categorical, numeric, text and date fields. It also has a ‘...
Read moreAI/ML Model Scoring - What Good Looks Like in Production
One of the main reasons why we build AI/Machine Learning models is for it to be used in production to support expert decision making. Whether your business is deciding what creatives your customers should be getting on emails or determining a product recommendation for a web page, AI/Models provide relevance/context to customers to drive ...
Read moreMachine Learning with H2O – the Benefits of VMware
This blog was originally posted by Justin Murray of VMware and can be accessed here. This brief article introduces a short 4.5 minute video that explains the reasons why VMware vSphere is a great platform for data scientists/engineers to use as their base operating platform. The video then demonstrates an example of this, showing a data...
Read moreHow to explain a model with H2O Driverless AI
The ability to explain and trust the outcome of an AI-driven business decision is now a crucial aspect of the data science journey. There are many tools in the marketplace that claim to provide transparency and interpretability around machine learning models but how does one actually explain a model? H2O Driverless AI provides robust inte...
Read moreBoosting your ROI with AutoML & Automatic Feature Engineering
If your business has started using AI/ML tools or just started to think about it, this blog is for you. Whether you are a data scientist, VP of data science or a line of a business owner, you are probably wondering how AI will impact your organization in various ways or why your current strategies are not working somehow. If you are not ...
Read moreWhat is Your AI Thinking? Part 3
In the past two posts we’ve learned a little about interpretable machine learning in general. In this post, we will focus on how to accomplish interpretable machine learning using H2O Driverless AI . To review, the past two posts discussed: Exploratory data analysis (EDA) Accurate and interpretable models Global explanations Local...
Read more8 Tips to Make AI Happen Without Getting Fired
“AI is the fastest growing workload on the planet,” Mike Gualtieri of Forrester Research.Last week, during H2O World San Francisco, we had the privilege to hear featured speaker Mike Gualtieri from Forrester Research offer tips on how to make AI happen without getting fired. This knowledge, he explained, was acquired by talking to enterp...
Read moreThe Journey of Pi and AI: An AI conference with heart
I was in San Francisco this (past) week as part of H2O World 2019. I flew in the week before and took a red-eye flight back home right after the conference on Tuesday night. Like any technology conference, this one had fantastic presentations, training, and product roadmap presentations. We even live streamed it if you couldn’t be there i...
Read moreKey Takeaways from the Gartner Magic Quadrant For Data Science & Machine Learning
The Gartner Magic Quadrant for Data Science and Machine Learning Platforms (Jan 2019) is out and H2O.ai has been named a Visionary. The Gartner MQ evaluates platforms that enable expert data scientists, citizen data scientists and application developers to create, deploy and manage their own advanced analytic models.H2O.ai Key Highlights...
Read moreWhat is Your AI Thinking? Part 2
Explaining AI to the Business PersonWelcome to part 2 of our blog series: What is Your AI Thinking? We will explore some of the most promising testing methods for enhancing trust in AI and machine learning models and systems. We will also cover the best practice of model documentation from a business and regulatory standpoint.More Techniq...
Read moreH2O New Year releases
There were two releases shortly after each other. First, on December 21st, there was a minor (fix) release 3.22.0.3 . Immediately followed by a more major release (but still on 3.22 branch) codename Xu, named after mathematician Jinchao Xu , whose work is focused on deep neural networks, besides many other fields of research.Of course, th...
Read moreWhat is Your AI Thinking? Part 1
Explaining AI to the Business PersonExplainable AI is in the news, and for good reason. Financial services companies have cited the ability to explain AI-based decisions as one of the critical roadblocks to further adoption of AI for their industry . Moreover, interpretability, fairness, and transparency of data-driven decision support sy...
Read moreFinally, You Can Plot H2O Decision Trees in R
Creating and plotting decision trees (like one below) for the models created in H2O will be the main objective of this post: Figure 1. Decision Tree Visualization in R Decision Trees with H2O With release 3.22.0.1 H2O-3 (a.k.a. open source H2O or simply H2O) added to its family of tree-based algorithms (which already included DR...
Read moreWhat Business Leaders Need to Know About AI
The interest around artificial intelligence (AI) is at an all-time fevered pitch right now, and it’s important to understand why.AI can solve real business problems and address very complex situations. Organizations and business leaders should start with the idea of how AI can help by identifying a business problem or use case that they c...
Read moreCelebrating our community and wins!
The last year was an amazing year at H2O.ai. We organized two H2O World’s, gathering thousands of attendees in person and online both in New York and London. Throughout the year, we garnered multiple industry awards and honors for AI and machine learning, but our customers received awards as well for the work they are doing with our techn...
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