Cloudera

FEBRUARY 25, 2021

AMPs move the starting line for any ML project by enabling data scientists to start with a full end-to-end project developed for a similar use case, including a trained and deployed ML model, as well as prebuilt predictive business applications, out of the box. The work of a machine learning model developer is highly complex.

Deep Learning 83

Deep Learning Machine Learning Forecasting Visualization 83

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. How the models are stored.

Data Science 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

O'Reilly on Data

MARCH 31, 2020

Pragmatically, machine learning is the part of AI that “works”: algorithms and techniques that you can implement now in real products. We won’t go into the mathematics or engineering of modern machine learning here. Machine learning adds uncertainty. This shift requires a fundamental change in your software engineering practice.

Management 332

Management Machine Learning Experimentation Metrics 332

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

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.

Modeling 64

Modeling IT Risk Management Deep Learning 64

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”. He was saying this doesn’t belong just in statistics. Key highlights from the session include.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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. OpenAI – Azure OpenAI as the foundational entity for creating GPT models and is based on Large Language Models (LLM). in next several years.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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

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. RStudio is an IDE for the R language used primarily for statistical analysis as well as data visualization.

Data Science 145

Data Science Visualization Modeling Enterprise 145

DataRobot

NOVEMBER 9, 2021

“One look is worth a Thousand Words” This phrase was used in 1913 to convey that graphics had a place in newspaper publishing. There are some interesting insights in adding unstructured features to the models. The dataset also provides centralized and windowed statistics features. Image courtesy towardsAI.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

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.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

We had big surprises at several turns and have subsequently published a series of reports. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). The first survey started as a simple exploration into mainstream adoption of machine learning (ML).

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Data Science and Beyond

OCTOBER 15, 2017

Here are my thoughts from 2014 on defining data science as the intersection of software engineering and statistics , and a more recent post on defining data science in 2018. The hardest parts of data science are problem definition and solution measurement, not model fitting and data cleaning , because counting things is hard.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

CONTACT Software

FEBRUARY 19, 2019

In line with this, Gartner has now published a “ Magic Quadrant for Data Science and Machine Learning Platforms “ The document itself can only be viewed behind a paywall, but on the net some of the companies mentioned in the report offer access to the document by entering the address.

Data Science 40

Data Science Statistics Machine Learning Deep Learning 40

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

Data Science Machine Learning Advertising Modeling 112

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. 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

Machine Learning Software Testing Technology 363