IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 94

Unstructured Data Cost-Benefit Experimentation Machine Learning 94

O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 362

Marketing Experimentation Metrics Testing 362

IBM Big Data Hub

APRIL 18, 2024

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Also, its emotional intelligence allows it to adapt communication to be empathetic and supportive, creating a more positive interaction for the customer.

Cost-Benefit 88

Cost-Benefit Modeling Manufacturing Interactive 88

IBM Big Data Hub

SEPTEMBER 6, 2023

Once trained, these bots can interact with customers no matter where they are on their customer journey, help resolve tickets quickly and effectively and increase customer satisfaction. AI can help marketers create and optimize content to meet the new standards.

Marketing 83

Marketing Technology Advertising ROI 83

CIO Business Intelligence

APRIL 26, 2022

Ever increasing advances in technology and continuous process optimization techniques have helped ensure that the global supply chain runs efficiently, turning raw materials into products that make their way to physical stores and ecommerce warehouses. How can we positively impact the employee or “people” experience?

Manufacturing 94

Manufacturing Optimization Metrics Deep Learning 94

bridgei2i

NOVEMBER 17, 2020

Data transformation: Use feature engineering through Computer Vision, Natural Language Processing, Graph Networks and other deep learning techniques to abstract and summarize information from a variety of sources ranging from image to text, voice, video, sensor and the like.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

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?

Deep Learning 59

Deep Learning Machine Learning Unstructured Data Modeling 59

CIO Business Intelligence

JANUARY 20, 2023

Understanding VDI As a virtual desktop solution, VDI enables remote workers to interact with an operating system and software the same way they would if working locally—on a network-delivered endpoint device. VDI adoption also comes with challenges—obstacles that can be overcome by following the right road map.

Technology 59

Technology Cost-Benefit Deep Learning Modeling 59

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. Here’s the higher-order-bit….

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

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. rule-based AI , machine learning , deep learning , etc.)

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

Smart Data Collective

MARCH 27, 2023

They have also started integrated computer vision and deep learning technology to identify inefficiencies. That’s the phrase tech folk use to describe how well various tools interact and communicate with one another. These tools will be well adapted for sharing data between departments and generally optimizing your operations.

Software 88

Software Finance Cost-Benefit Data-driven 88

Decision Management Solutions

FEBRUARY 8, 2021

As you’ll see, the development of this amazing, one-of-a-kind vessel led to a conclusion that we at Decision Management Solutions see every day in our client work: It’s never enough to just rely on artificial intelligence (AI)/machine learning (ML) to do all the decision-making.

Machine Learning 93

Machine Learning Testing Deep Learning Optimization 93

IBM Big Data Hub

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. Use this to build a question-answering interface grounded on specific content and recommend optimal next steps to provide customer service assistance. That sounds like a joke, but we’re quite serious.

Modeling 90

Modeling Data Lake Enterprise Deep Learning 90

IBM Big Data Hub

JULY 17, 2023

Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. Enterprise organizations (many of whom have already embarked on their AI journeys) are eager to harness the power of generative AI for customer service.

Consulting 56

Consulting Machine Learning Deep Learning Cost-Benefit 56

bridgei2i

APRIL 16, 2021

Anil: Deep learning systems are essentially large networks with many layers constituting an artificial neuron that fires when a certain set of its input neurons fire. But does nobody really understand how deep learning actually works? But deep neural networks are complex systems, which are hard to understand.

Deep Learning 98

Deep Learning Machine Learning Digital Transformation Software 98

O'Reilly on Data

JUNE 18, 2019

Even if we boosted the quality of the available data via unification and cleaning, it still might not be enough to power the even more complex analytics and predictions models (often built as a deep learning model). Data programming. An important paradigm for solving both these problems is the concept of data programming.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Domino Data Lab

JULY 28, 2021

It is the job of a data scientist to navigate these subtle differences, pick the model that aligns best with the problem statement, optimize and monitor performance and translate the findings back into a business context. These changes often personify themselves as square roots, lambdas or inverted matrices. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

CIO Business Intelligence

APRIL 4, 2022

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. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Technology 52

Technology Deep Learning Cost-Benefit Data Quality 52

Domino Data Lab

JULY 28, 2021

Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions. In fact, deep learning was first described theoretically in 1943. Reinforcement learning focuses on optimizing a specific decision. None of these techniques are new.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Jen Stirrup

MAY 5, 2020

You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics. Apache Spark also allows you to do Machine Learning, streaming analytics, interactive querying, and also data visualization, as well. 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

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Let’s get started.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Smart Data Collective

APRIL 3, 2020

With the help of chatbots, you can interact with your customers even if you are sleeping. A couple of months ago, Hacker Moon wrote a great article on the use of deep learning to create chatbot s. You may want to spend one to two minutes explaining what you have to offer, and they might ask some follow-up questions.

Big Data 94

Big Data Data-driven Data mining Software 94

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

bridgei2i

DECEMBER 15, 2021

With significant adoption among industries as well as personal lives, AI is impacting enterprise transformation at scale, whilst changing the way humans interact with machines. Artificial Intelligence (AI) has reached a state of pervasiveness in everyday life. With the world having 1.1 billion broadband connections and 4.5 billion by 2025.[1]

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

Smart Data Collective

APRIL 3, 2020

With the help of chatbots, you can interact with your customers even if you are sleeping. A couple of months ago, Hacker Moon wrote a great article on the use of deep learning to create chatbot s. You may want to spend one to two minutes explaining what you have to offer, and they might ask some follow-up questions.

Big Data 80

Big Data Data-driven Data mining Software 80

Insight

APRIL 9, 2019

For industries outside of tech, ML can be utilized to personalize a user’s experience, automate laborious tasks and optimize subjective decision making. It is an optimization problem done by many trials. Multi-disciplinary product managers, however, are well-equipped to tackle this very challenge. It is far from an automated process.

Manufacturing 75

Manufacturing Machine Learning Testing Software 75

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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

Machine Learning Big Data Data Science Data Warehouse 44

Cloudera

NOVEMBER 15, 2021

Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful. The other is less well defined but points towards innovation opportunities to extend, refine and optimize technologies originally designed for structured data, and make them better suited for unstructured data. .

Unstructured Data 85

Unstructured Data Recreation/Entertainment Structured Data Reporting 85

O'Reilly on Data

JUNE 7, 2022

And granted, a lot can be done to optimize training (and DeepMind has done a lot of work on models that require less energy). That’s an allusion to the debate ( sometimes on Twitter ) between LeCun and Gary Marcus, who has argued many times that combining deep learning with symbolic reasoning is the only way for AI to progress. (In

Modeling 363

Modeling Interactive Optimization Deep Learning 363

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

TF Lattice offers semantic regularizers that can be applied to models of varying complexity, from simple Generalized Additive Models, to flexible fully interacting models called lattices, to deep models that mix in arbitrary TF and Keras layers. The drawback of GAMs is that they do not allow feature interactions.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

CIO Business Intelligence

DECEMBER 1, 2023

We did a major pivot because this was a game changer in terms of its interactive abilities, as well as the comprehensiveness of its answers and its data generation capabilities. We will pick the optimal LLM. We’ll take the optimal model to answer the question that the customer asks.” We were all-hands-on-deck,” Reihl says. “We

Cost-Benefit 123

Cost-Benefit Digital Transformation Machine Learning Optimization 123

Smarten

APRIL 19, 2024

Benefits include customized and optimized models, data, parameters and tuning. Price and bundling optimization, demand pricing, and other variables will be included to provide the best options, prices and responses and to personalize the approach and present results for data analysis and for end users.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters.

Machine Learning 79

Machine Learning Modeling Deep Learning Predictive Modeling 79

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.

Deep Learning 115

Deep Learning Machine Learning Data Science Cost-Benefit 115

AWS Big Data

OCTOBER 26, 2023

Some recent examples of performance optimizations driven by fleet telemetry include: String query optimizations – By analyzing how Amazon Redshift processed different data types in the Redshift fleet, we found that optimizing string-heavy queries would bring significant benefit to our customers’ workloads.

Data Warehouse 91

Data Warehouse Cost-Benefit Dashboards Optimization 91

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. Essential Theory of Reinforcement Learning.

Optimization 111

Optimization Modeling Deep Learning Metrics 111