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. All sans human-control.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

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. More traditional modes also saw increases: usage of books increased by 11%, while videos were up 24%.

Machine Learning 363

Machine Learning Software Testing Technology 363

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

Edwin Chen

OCTOBER 6, 2014

Metrics like CTR, or even number of favorites and retweets, will probably optimize for showing quick one-liners and pictures of funny cats. So why, so often, do we never try to measure the relevance of our models? In particular, I'll use the example of related book suggestions on Amazon as I walk through the rest of this post.

Metrics 79

Metrics Measurement Machine Learning Testing 79

Domino Data Lab

MARCH 3, 2019

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). What’s been the impact of using ML models on culture and organization? Who builds their models?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

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. What types of projects can open source LLM models enable?

Risk 91

Risk Modeling Cost-Benefit Enterprise 91

Occam's Razor

OCTOBER 12, 2017

Optimal Starting SCOTUS Starting Points. Some cases are very dear to me, I truly love them, there is a lot to learn from them as you explore the back and forth of the debate, the majority opinion and the dissenting one (or ones). Here are the collection of books, videos, people and learning opportunities from my sweetspot….

Marketing 136

Marketing Analytics Machine Learning Strategy 136

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

datapine

NOVEMBER 19, 2019

There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience.

Technology 279

Technology Internet of Things IT IoT 279

IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 56

Modeling Cost-Benefit Data Lake Machine Learning 56

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”. Also, these surveys, these are mini books: if you want to grab them, they are free downloads.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 351

IT Testing Experimentation Software 351