Rocket-Powered Data Science

JULY 6, 2023

For a short introduction to generative AI, see my article “ Generative AI – Chapter 1, Page 1 ”. The AI conversations, especially in technical circles, have focused intensively on generative AI, the creation of written content, images, videos, marketing copy, software code, speeches, and countless other things.

Strategy 153

Strategy Enterprise Software Marketing 153

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.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 119

Enterprise Modeling Testing Data-driven 119

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. Its value is so significant that scaling data science has become the new business imperative with organizations spending tens of millions of dollars on data, technology and talent. What is Data Science and How is it Used?

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

FineReport

DECEMBER 19, 2019

Generally, companies will store data in local databases or public clouds. and others will use big data storage format like HBase and Parquet. I will recommend beginners to learn SQL well, and then get to know about HBase and Parquet as needed. Pandas is a Python data science library that is constantly improving.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

O'Reilly on Data

MARCH 20, 2019

Watermarking is a term borrowed from the deep learning security literature that often refers to putting special pixels into an image to trigger a desired outcome from your model. It seems entirely possible to do the same with customer or transactional data. Watermark attacks.

Modeling 227

Modeling Machine Learning Predictive Modeling Consulting 227

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

Domino Data Lab

MARCH 3, 2019

We had big surprises at several turns and have subsequently published a series of reports. Seriously, this entire article merely skims the surface of those reports. Check the end of this article for key guidance synthesized from the practices of the leaders in the field. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

O'Reilly on Data

JANUARY 25, 2021

AI, Machine Learning, and Data. Healthy growth in artificial intelligence has continued: machine learning is up 14%, while AI is up 64%; data science is up 16%, and statistics is up 47%. We informally define machine learning as “the part of AI that works”; AI itself is more research oriented and aspirational.

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. Having more data is generally better; however, there are subtle nuances.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JUNE 23, 2019

It used deep learning to build an automated question answering system and a knowledge base based on that information. It is like the Google knowledge graph with all those smart, intelligent cards and the ability to create your own cards out of your own data. That’s a good article by Steven Levy about this.

Management 110

Management Machine Learning Experimentation Metrics 110