Decision Management Solutions

JANUARY 16, 2020

The Machine Learning Times (previously Predictive Analytics Times) is the only full-scale content portal devoted exclusively to predictive analytics. ” In his article, Eric warns, “Predictive models often fail to launch. ” In his article, Eric warns, “Predictive models often fail to launch.

Machine Learning 87

Machine Learning Predictive Modeling Predictive Analytics Deep Learning 87

Analytics Vidhya

JUNE 29, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Did you developed a Machine Learning or Deep Learning application. The post Deploy Your ML/DL Streamlit Application on Heroku appeared first on Analytics Vidhya.

Deep Learning 155

Deep Learning Machine Learning Data Science Publishing 155

DataRobot

FEBRUARY 10, 2021

Machine learning is a glass cannon. Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. 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

Cloudera

SEPTEMBER 20, 2022

This blog is intended to serve as an ethics sheet for the task of AI-assisted comic book art generation, inspired by “ Ethics Sheets for AI Tasks.” AI-assisted comic book art generation is a task I proposed in a blog post I authored on behalf of my employer, Cloudera. Introduction. Scope, motivation, and benefits.

Deep Learning 87

Deep Learning Cost-Benefit Risk Data-driven 87

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Transformer models take applications such as language translation and chatbots to a new level.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

Sisense

APRIL 10, 2020

We are surrounded by written text every day: emails, SMS messages, webpages, books, and much more. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smart Data Collective

FEBRUARY 15, 2022

In the past, people usually plagiarized content out of books. They would have to go through every possible book they could think of to identify passages that students or other authors might have copied. “So, We can build our plagiarism checker that searches a vast database for stolen content using machine learning.

Machine Learning 116

Machine Learning Deep Learning Software Technology 116

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Machine Learning | Marketing.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

CIO Business Intelligence

JUNE 12, 2023

It can be about anything from classic data analysis and advanced data analysis, to robotics or machine learning. The vast majority of companies already have a structure for analytics and machine learning, so we’re already there; it doesn’t add much,” she adds. It’s all called AI, she says. I didn’t think it could be more.

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

CDW Research Hub

JULY 31, 2019

For instance, a level 1 travel bot can provide a link for you to book travel. Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. An intent is something that a user is trying to convey or accomplish.

Deep Learning 49

Deep Learning Machine Learning Testing Modeling 49

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

Edwin Chen

OCTOBER 6, 2014

So why, so often, do we never try to measure the relevance of our models? I'm a big fan of man-in-the-machine techniques , so to get around this problem, I'm going to talk about a human evaluation approach to measuring the performance of personalization and discovery products. This book was so beautifully written.

Metrics 79

Metrics Measurement Machine Learning Testing 79

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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 104

Risk Modeling Cost-Benefit Enterprise 104

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 62

Modeling Cost-Benefit Data Lake Machine Learning 62

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. However, the concept is quite abstract.

IT 346

IT Testing Experimentation Software 346

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.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. Introduction. The contents will cover.

Optimization 111

Optimization Modeling Deep Learning Metrics 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. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). Who builds their models? Introduction.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. 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

JANUARY 17, 2024

More advanced chatbots use machine learning , artificial intelligence (AI) and generative AI technology to generate real-time responses based on user input. AI-powered bots leverage machine learning and NLP ( natural language processing ) to understand prompts and context.

Interactive 69

Interactive Sales Machine Learning Marketing 69

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

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%. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Occam's Razor

OCTOBER 12, 2017

It is still on the books, and places extraordinary power in the President of the US to do what they want to people who might not look like "Americans." Here are the collection of books, videos, people and learning opportunities from my sweetspot…. I want to recommend three books. Intro to Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136