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?

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O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.

Machine Learning 238

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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.

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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. billion by 2030.

Enterprise 107

Enterprise Interactive Data-driven Key Performance Indicator 107

Corinium

JUNE 6, 2019

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. There is usually a steep learning curve in terms of “doing AI right”, which is invaluable. What is the most common mistake people make around data?

Insurance 250

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O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0

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CIO Business Intelligence

JANUARY 23, 2023

As OpenAI’s exclusive cloud provider it will see additional revenue for its Azure services, as one of OpenAI’s biggest costs is providing the computing capacity to train and run its AI models. That app, Microsoft Designer , is currently in closed beta test. The deal, announced by OpenAI and Microsoft on Jan.

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The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

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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.

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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.

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CIO Business Intelligence

APRIL 25, 2022

The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. It culminates with a capstone project that requires creating a machine learning model. On-site courses are available in Munich. Remote courses are also available. Switchup rating: 5.0 (out

Data Science 145

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IBM Big Data Hub

JULY 11, 2023

This sort of routine monitoring and scheduling takes tasks off the hands of clinical staff, who can then spend more time directly on patient care, where human judgment and interaction matter most. In some instances, such as identifying cardiomegaly in chest X-rays, they found that a hybrid human-AI model produced the best results.

Deep Learning 60

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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.

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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.

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Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal. Computer Science Skills.

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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.

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Decision Management Solutions

FEBRUARY 8, 2021

in partnership with IBM and other organizations is in the process of conducting performance tests on the world’s first autonomous ship and is due to set sail for its first transatlantic voyage this spring. It’s made up of a series of different systems operating and interacting with each other. Marine AI—based in Plymouth, U.K.—in

Machine Learning 93

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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?

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Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. Today, we’re developing AI in an era where data is treated as code, or at least as an extension of code, because the code alone cannot achieve deep learning without the data. When building your data model, it’s vital to avoid both underfitting and overfitting.

Management 95

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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. 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

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Domino Data Lab

OCTOBER 7, 2020

MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. Statistics developed in the last century are based on probability models (distributions). The accuracy of any predictive model approaches 100%.

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IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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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

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CDW Research Hub

JULY 31, 2019

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

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Domino Data Lab

JULY 28, 2021

In its current form , data science is limitless in terms of industry and application; the only requirement is data, compute power, data scientists, and a desire to become model-driven. Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions.

Data Science 45

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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.

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CIO Business Intelligence

APRIL 4, 2022

The confines of tabular data models and rigid schemas make it difficult to add new or different kinds of connections. If a specific email or login credential is identified in a potentially fraudulent transaction, all future interactions with this email or credential can be subject to additional scrutiny. Real-time Fraud Detection.

Technology 52

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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.

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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

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Domino Data Lab

JUNE 23, 2019

Be aware that machine learning often involves working on something that isn’t guaranteed to work. As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. It is similar to R&D. Transcript.

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Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Model-Driven Data Queries. of relational databases represent early forms of machine learning.

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Domino Data Lab

MARCH 29, 2021

Some of the key benefits of using Spark for machine learning include: Distributed Learning – Parallelize compute-heavy workloads such as distributed training or hyper-parameter tuning Interactive Exploratory Analysis – Efficiently load large data sets in a distributed manner. GPU) and use bitnami/spark:2.4.6

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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

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O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more. If we had AGI, how would we know it?

Modeling 363

Modeling Interactive Optimization Deep Learning 363

Cloudera

SEPTEMBER 12, 2018

Commonwealth Bank of Australia worked with Cloudera to implement a modern data platform with an AI-powered customer decisioning layer that dramatically improves how the bank interacts with its customers. The bank brought together 27 billion data points and uses AI to understand the next-best conversation 21 million times each weekday.

Machine Learning 44

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DataRobot Blog

FEBRUARY 2, 2023

Large language models, also known as foundation models, have gained significant traction in the field of machine learning. These models are pre-trained on large datasets, which allows them to perform well on a variety of tasks without requiring as much training data. What Are Large Language Models?

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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.

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