O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. That’s where remediation strategies come in.

Machine Learning 190

Machine Learning Modeling Testing Risk Management 190

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning can be surprisingly useful when it comes to monetizing apps.

Machine Learning 88

Machine Learning Data mining Advertising Deep Learning 88

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

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

TDAN

AUGUST 6, 2019

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

Deep Learning 81

Deep Learning Technology Data Architecture Metadata 81

CIO Business Intelligence

OCTOBER 13, 2023

Here are the top 11 roles companies are currently hiring for, or have plans to hire for, to directly address their emerging gen AI strategies. This role is responsible for training, developing, deploying, scheduling, monitoring, and improving scalable machine learning solutions in the enterprise.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. that support unsupervised learning. What’s driving this growth?

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. 3) Concept drift by COVID – as mentioned above, concept drift is being addressed in machine learning and data science projects by MLOps, but concept drift so much bigger than MLOps.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Rocket-Powered Data Science

JULY 13, 2023

Insights discovery (powered by analytics, data science, and machine learning) drives next-best decisions, next-best actions, and business process automation. But faster analytics (including data science and machine learning) needs faster access to more data, in order to answer many of those questions that we just listed.

Analytics 166

Analytics Machine Learning Deep Learning Data Science 166

datapine

MAY 14, 2019

Best for: Those looking for a practical means of understanding how artificial intelligence serves to enhance data science and use this knowledge to improve their data analytics strategies. 2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. 4) “Machine Learning Yearning” by Andrew Ng.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

CIO Business Intelligence

JANUARY 26, 2024

Carnegie Mellon University The Machine Learning Department of the School of Computer Science at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning.

Machine Learning 99

Machine Learning Statistics Recreation/Entertainment Data Science 99

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 122

Data Science Machine Learning Predictive Modeling Experimentation 122

CDW Research Hub

AUGUST 21, 2019

Organizations across all industries are seeing the value and competitive advantage of having an artificial intelligence (AI) strategy. The challenges of implementing an AI strategy are many. The combination of Watson Machine Learning Accelerator and AC922 servers reduces AI deployment times from weeks and months, down to hours.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

Smart Data Collective

JUNE 10, 2022

Machine Learning Engineer. As a machine learning engineer, you would create data funnels and deliver software solutions. As well as designing and building machine learning systems, you could be responsible for running tests and monitoring the functionality and performance of systems. Data Architect.

Data Science 117

Data Science Machine Learning Statistics Business Intelligence 117

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

Cloudera

FEBRUARY 25, 2021

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. The work of a machine learning model developer is highly complex.

Deep Learning 81

Deep Learning Machine Learning Forecasting Visualization 81

CIO Business Intelligence

MAY 20, 2022

The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. Carnegie Mellon University.

Machine Learning 144

Machine Learning Statistics Recreation/Entertainment Data Science 144

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? Just starting out with analytics?

Machine Learning 125

Machine Learning Enterprise Deep Learning Cost-Benefit 125

DataRobot

JULY 27, 2021

We have long aspired to be the preeminent leader in MLOps with our focus on Applied AI and our strategy to get every model into production, then managing and continuously updating models to ensure peak performance over time. For this reason, Algorithmia is the perfect complement to DataRobot’s full end-to-end solution. We couldn’t agree more.

Optimization 98

Optimization Modeling Machine Learning Deep Learning 98

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. My personal strategy: Understand reality. Invest in continuous learning. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Rinse and repeat.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

APRIL 22, 2024

We believe there are three core areas that every organization should focus on: sustainability strategy and reporting; energy transition and climate resilience; and intelligent asset, facility and infrastructure management. This approach can help organizations to more easily establish a sustainability strategy across the business.

IoT 83

IoT Internet of Things Cost-Benefit Reporting 83

IBM Big Data Hub

DECEMBER 5, 2023

Retailers recognize the need to build their strategies around AI, integrating it into many aspects of their operations. With these tools at their disposal retailers are well-positioned to embrace generative AI as an integral part of their strategies and will be equipped to navigate the increasingly complex and fast-paced consumer landscape.

Unstructured Data 94

Unstructured Data Cost-Benefit Experimentation Machine Learning 94

CIO Business Intelligence

JANUARY 13, 2023

Software-based advanced analytics — including big data, machine learning, behavior analytics, deep learning and, eventually, artificial intelligence. Unfortunately, defense has continued to employ a strategy based mostly on human decision-making and manual responses taken after threat activities have occurred.

Software 133

Software Machine Learning Behavioral Analytics Risk 133

Smart Data Collective

JANUARY 14, 2022

Computer systems capable of learning, reasoning, and acting are still in the early stages. Machine learning needs massive amounts of data. A few years ago, a Google study discovered that machine learning-based optical character recognition (OCR) technology could handle 99.8 Automated Attacks.

Machine Learning 125

Machine Learning Deep Learning Strategy Data-driven 125

CIO Business Intelligence

SEPTEMBER 19, 2023

AI personalization utilizes data, customer engagement, deep learning, natural language processing, machine learning, and more to curate highly tailored experiences to end-users and customers. Artificial Intelligence, Chatbots, IT Strategy, Predictive Analytics

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

bridgei2i

OCTOBER 7, 2020

Adoption of Automated Sales & Underwriting Strategies can Transform Insurance. A digital transformation of underwriting with automation can make it easier to navigate the complexity of data with the help of AI-powered technologies like machine-learning (ML), deep learning (DL), OCR, CV and NLP, etc to estimate the risk impact.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. Given enough trials and data, Machine Learning techniques are likely to add great value in the forecasting process.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

CIO Business Intelligence

JUNE 1, 2022

These supercomputers power exciting innovations in deep learning, disease control, and physics—think bionic eyes, DNA sequencing for infectious disease research, and the study of time crystals. . CSIRO’s Bracewell Delivers Deep Learning, Bionic Vision. Bracewell’s IO500 score was 99.64, IO500 BW 39.90

Deep Learning 85

Deep Learning Snapshot Optimization Data Quality 85

CIO Business Intelligence

JUNE 21, 2022

Real-time big data analytics, deep learning, and modeling and simulation are newer uses of HPC that governments are embracing for a variety of applications. Deep learning, together with machine learning, is able to detect cyber threats faster and more efficiently. . New Applications, New Architectures.

Deep Learning 94

Deep Learning Big Data ROI Software 94

bridgei2i

FEBRUARY 21, 2020

Deep learning provides an edge over your competition. Using machine learning and historical data, future trends and patterns can be predicted depending on your area of concern. Using machine learning and historical data, future trends and patterns can be predicted depending on your area of concern.

IoT 83

IoT Analytics Deep Learning B2B 83

David Menninger's Analyst Perspectives

APRIL 11, 2024

I recently attended the Salesforce Trailblazer DX event to learn more about Salesforce’s artificial intelligence products and strategy. Fueled by generative AI, awareness and investment in AI seems to be exploding. ISG research shows that enterprises plan to nearly triple the portion of budgets allocated to AI over the next two years.

Enterprise 144

Enterprise Strategy Deep Learning Machine Learning 144

CIO Business Intelligence

MARCH 9, 2022

Data analytics platforms that leverage artificial intelligence (AI) and machine learning (ML) can help organizations derive insights from their data at scale to help build deeper customer relationships, run more efficient operations and pivot with new innovations. Ready to evolve your analytics strategy or improve your data quality?

Data-driven 86

Data-driven Analytics Machine Learning Optimization 86

datapine

AUGUST 14, 2019

Companies surely need data scientists to help them empower their analytics processes, build a numbers-based strategy that will boost their bottom line, and ensure that enormous amounts of data are translated into actionable insights. But being an inquisitive Sherlock Holmes of data is no easy task. Source: RStudio.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

AUGUST 28, 2023

With nearly 5 billion users worldwide—more than 60% of the global population —social media platforms have become a vast source of data that businesses can leverage for improved customer satisfaction, better marketing strategies and faster overall business growth.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. The resulting structured data is then used to train a machine learning algorithm. There are a lot of image annotation techniques that can make the process more efficient with deep learning.

Metrics 63

Metrics Machine Learning Uncertainty Deep Learning 63

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 94

IT Digital Transformation IoT Cost-Benefit 94