DataRobot

FEBRUARY 10, 2021

Machine learning is a glass cannon. The promise and power of AI lead many researchers to gloss over the ways in which things can go wrong when building and operationalizing machine learning models. 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

Insight

SEPTEMBER 20, 2019

The model is optimized for recall in order to reduce the false negative. Discussion In this project, I used deep learning techniques to automatically detect lesion regions and classify the lesion, which can have both cost and time-saving benefits. The results of the testing dataset are shown in the following confusion matrix.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

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. billion in 2022, according to a research study published by The Insight Partners in August 2022.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

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 58

Data Science Machine Learning Cost-Benefit Deep Learning 58

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

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. Machine learning applications rely on three main components: models, data, and compute.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Smart Data Collective

FEBRUARY 20, 2022

Its cost-effective service solutions ensure that you can optimize costs, organize data, and provide access controls to meet your business, organizational, and regulatory needs. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms. Management of data.

Cost-Benefit 117

Cost-Benefit Data Lake Software Machine Learning 117

Insight

APRIL 9, 2019

NASA [Public domain] In this blog, I’ll discuss how I worked collaboratively with various domain experts, using reinforcement learning to develop innovative solutions in rocket engine development. In doing so, I’ll demonstrate the application of ML techniques to the manufacturing industry and the role of the Machine Learning Product Manager.

Manufacturing 75

Manufacturing Machine Learning Testing Software 75

bridgei2i

APRIL 16, 2021

He has over a decade of experience in the field of AI, which he started with his paper on machine learning in 2009. He has published over eight papers on computer vision. He has published over eight papers on computer vision. But does nobody really understand how deep learning actually works?

Deep Learning 98

Deep Learning Machine Learning Digital Transformation Software 98

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. But for most enterprise, using machine learning…not really.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Cloudera

SEPTEMBER 12, 2018

The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Enterprise Machine Learning: . It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. Societal Impact: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Insight

MARCH 5, 2019

Internet of Thing (AWS IoT) Are you looking to transition into the field of machine learning in Silicon Valley, New York, or Toronto? Apply for the upcoming June session today ( Deadline is March 25th for SV and NYC ) or learn more about the Artificial Intelligence program at Insight!

Machine Learning 71

Machine Learning Internet of Things Recreation/Entertainment IoT 71

Smarten

APRIL 19, 2024

The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Benefits include customized and optimized models, data, parameters and tuning. billion, with the market growing by 31.1% in next several years.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Cloudera

SEPTEMBER 11, 2020

What they have learned is that often their legacy Machine Learning models (e.g. The need to start better leveraging external data, working with broader data sets inclusive of incremental ‘demand signals,’ is no longer a ‘nice to have’ in order to improve forecast accuracy and inventory optimization.

Manufacturing 92

Manufacturing Forecasting Digital Transformation Sales 92

Insight

JANUARY 14, 2020

Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow. Choosing your loss function and optimizer Finally, in the last block of code, we must compile the model that we just built.

Metrics 58

Metrics Optimization Modeling Testing 58

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 119

Deep Learning Machine Learning Data Science Cost-Benefit 119

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 92

Data Warehouse Cost-Benefit Dashboards Optimization 92

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

IBM Big Data Hub

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content.

Risk 101

Risk Modeling Cost-Benefit Enterprise 101

Domino Data Lab

MAY 8, 2019

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. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

AUGUST 28, 2017

Over the last couple years, I’ve spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). The first related to pure deep learning and its amazingness, I was familiar with this one. Pretty damn fast. It truly is mind-blowing.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

Domino Data Lab

MARCH 29, 2021

The addition of the MLlib library, consisting of common learning algorithms and utilities, opened up Spark for a wide range of machine learning tasks and paved the way for running complex machine learning workflows on top of Apache Spark clusters. A benchmark published by Nvidia shows 3.8x

Cost-Benefit 98

Cost-Benefit Machine Learning Testing Interactive 98

BizAcuity

MARCH 31, 2022

There have been so many articles published about AI and its applications, you can find millions of articles from broad concepts to deep technical literature on the internet. Marketers also have access to several AI softwares to save time and optimize their work at every step of the funnel. AI in Healthcare. AI Services.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

CIO Business Intelligence

JANUARY 31, 2023

Telecommunications, manufacturing, retail, publishing, and others have seen amazing changes in terms of new opportunities, capabilities, and efficiencies. These changes bring new challenges, but advancements in IT automation, artificial intelligence (AI) and machine learning (ML), and edge-computing capabilities will play a key role.

Deep Learning 111

Deep Learning Cost-Benefit Data-driven Manufacturing 111

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. We had big surprises at several turns and have subsequently published a series of reports. In order, those are: “5 findings from O’Reilly’s machine learning adoption survey companies should know”. “

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Insight

MARCH 28, 2019

Like Derek, the first step Yanxia took was to classify each review’s sentences into topic categories, but she opted to use a machine learning-based approach to identify 14 latent topics. After his time at Insight, John was hired by Deep Macro as a data scientist. Yanxia Li earned her Ph.D. John Phillips holds a Ph.D.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 40; it peaked at Strata NY 2018 at No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

O'Reilly on Data

JANUARY 25, 2021

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. AI, Machine Learning, and Data. Artificial intelligence, machine learning, and data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Occam's Razor

OCTOBER 12, 2017

The first two are from editions of my newsletter, The Marketing – Analytics Intersect (it goes out weekly, and is now my primary publishing channel, sign up!). Optimal Starting SCOTUS Starting Points. Intro to Machine Learning. Machine Learning. Deep Learning. The answer was, yes.).

Marketing 136

Marketing Analytics Machine Learning Strategy 136