Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. Parameter Optimization.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. What is Machine Learning. Instead, they are learned by training a model on data.

Machine Learning 96

Machine Learning Sales Data Science Modeling 96

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

CIO Business Intelligence

JANUARY 24, 2024

Generative AI and large language models (LLMs) like ChatGPT are only one aspect of AI. It’s the culmination of a decade of work on deep learning AI. Model sizes: ~5 billion to >1 trillion parameters. Model sizes: ~Millions to billions of parameters. AI encompasses many things.

Deep Learning 112

Deep Learning Unstructured Data Machine Learning Modeling 112

Smart Data Collective

NOVEMBER 1, 2020

Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? Source ].

Machine Learning 134

Machine Learning Data mining Visualization Statistics 134

DataRobot

JULY 27, 2021

In a global marketplace where decision-making needs to happen with increasing velocity, data science teams often need not only to speed up their modeling deployment but also do it at scale across their entire enterprise. This allows for the pipelining of incredibly complex inference models.

Optimization 98

Optimization Modeling Machine Learning Deep Learning 98

Cloudera

APRIL 10, 2021

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. To overcome this, practitioners often turn to NVIDIA GPUs to accelerate machine learning and deep learning workloads. .

Machine Learning 63

Machine Learning Modeling Cost-Benefit Data Science 63

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. Many stock market transactions use ML.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Domino Data Lab

JULY 10, 2019

New tools are constantly being added to the deep learning ecosystem. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow data scientists to speed up research.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

DataRobot

FEBRUARY 10, 2021

Machine learning is a glass cannon. Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. As a data scientist, one of my passions is to reproduce research papers as a learning exercise.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

Analytics Vidhya

APRIL 11, 2024

Employing a tiered approach empowers individuals and organizations to select the optimal model aligning with their specific requirements. Introduction Anthropic’s Claude 3 API ushers in a new era of artificial intelligence, offering a comprehensive suite of AI assistants tailored to diverse user needs.

Modeling 247

Modeling Optimization Analytics Deep Learning 247

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” Karpathy suggests something radically different: with machine learning, we can stop thinking of programming as writing a step of instructions in a programming language like C or Java or Python. Instead, we can program by example.

Software 261

Software Machine Learning Risk Data-driven 261

Smarten

JUNE 14, 2023

GPT, or Generative Pre-Trained Transformer, is a Large Language Model (LLM). GPT-4 has a capacity of more than 175 billion machine learning parameters, and can support many types of tasks, e.g., answering questions, providing machine translation, summarizing text, time series forecasting, etc.

Optimization 52

Optimization IT Digital Transformation Consulting 52

CIO Business Intelligence

SEPTEMBER 19, 2023

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

Rocket-Powered Data Science

DECEMBER 15, 2018

This wisdom applies not only to life but to machine learning also. Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. A related problem also arises in unsupervised machine learning.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

Jen Stirrup

MAY 5, 2020

You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics. 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 Azure Data Lake Store is an optimized way of storing data, especially for analytics.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Domino Data Lab

FEBRUARY 10, 2019

This blog post provides insights into why machine learning teams have challenges with managing machine learning projects. Why are Machine Learning Projects so Hard to Manage? I’ve watched lots of companies attempt to deploy machine learning?—?some Why is this?

Machine Learning 63

Machine Learning Modeling Deep Learning Metrics 63

Data Science 101

FEBRUARY 15, 2020

Announcements around an exciting new open-source deep learning library, a new data challenge and more. Microsoft Releases DeepSpeed for Training very large Models DeepSpeed is a new open-source library for deep learning optimization. An Intuitive Approach to Machine Learning Models.

Data Science 112

Data Science Deep Learning Machine Learning Modeling 112

DataRobot Blog

AUGUST 3, 2022

How can you save time in understanding the impact of language when working with text in ML models ? With tens of thousands of Text AI projects, DataRobot has helped organizations unlock insights from text and generate predictions with text models—from assisting with customer support ticket triage to predicting real estate sale prices.

Machine Learning 105

Machine Learning Optimization Deep Learning Modeling 105

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 332

Management Machine Learning Experimentation Metrics 332

Insight

SEPTEMBER 20, 2019

The model was a modified U-Net and trained on GPU hosted by Amazon Web Services (AWS) EC2 instances. The loss function used is illustrated in the figure below, with “A” representing the ground truth (manually labeled mask) and “B” representing the model generated mask. Here, we built a model to mimic this process. on test data.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

CIO Business Intelligence

FEBRUARY 22, 2024

There’s no defined hierarchical structure, but the Hub is based on a transversal and collaborative model where groups are created, and employees from all areas work on specific projects along with external experts. One of the main strategic transversal areas is AI. With this in mind, the AI ​​CoE acts along two clear lines at a global level.

IT 105

IT Digital Transformation IoT Cost-Benefit 105

Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. These data models predict outcomes of new data. Programming knowledge is needed for the typical tasks of transforming data, creating graphs, and creating data models. Basics of Machine Learning. In supervised learning, a variable is predicted.

Data Science 105

Data Science Statistics Deep Learning Machine Learning 105

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

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

CIO Business Intelligence

APRIL 25, 2022

Enterprises are betting big on machine learning (ML). According to IDC , 85% of the world’s largest organizations will be using artificial intelligence (AI) — including machine learning (ML), natural language processing (NLP) and pattern recognition — by 2026. So what’s the problem? The problem with ML.

Machine Learning 134

Machine Learning Enterprise Deep Learning Cost-Benefit 134

CIO Business Intelligence

JUNE 2, 2022

Among the hot technologies, artificial intelligence and machine learning — a subset of AI that that makes more accurate forecasts and analysis as it ingests data — continue to be of high interest as banks keep a strong focus on costs while trying to boost customer experience and revenue.

Predictive Analytics 145

Predictive Analytics Technology Analytics Machine Learning 145

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 87

Metrics Machine Learning Risk Statistics 87

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. If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

IBM Big Data Hub

APRIL 22, 2024

The platform, created in partnership with Andel Energi in Denmark, uses IoT sensors, AI and the cloud to provide an energy ecosystem for consumers to participate in real-time, intelligent grid optimization. These models also help estimate where carbon is stored, how long it will take to degrade, and more.

IoT 84

IoT Internet of Things Cost-Benefit Reporting 84

Smart Data Collective

SEPTEMBER 30, 2021

This speed of vaccine development was also possible due to AI models that served researchers in analyzing vast amounts of coronavirus data. Machine learning was able to sort through this enormous amount of data and predict which subcomponents are the most immunogenic ones. Quantum Computing.

Deep Learning 97

Deep Learning Machine Learning Business Objectives Testing 97

CIO Business Intelligence

JUNE 21, 2022

federal government, HPC is being used to accelerate basic science, develop therapeutics and other treatments for COVID-19, perform military applications such as simulations, handle climate and weather modeling, and a myriad of other tasks in diverse agencies. . Within the U.S. Big data analytics is being used to uncover crimes. In the U.S.,

Deep Learning 111

Deep Learning Big Data ROI Software 111

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. For such processes, the data scientist can define and solve a mathematical model to optimize the defined goals.

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84