O'Reilly Media

APRIL 5, 2023

Worse yet, the AI’s bias would likely find its way into the system’s database and follow the students from one class to the next. In 2016, Microsoft’s Tay chatbot was shut down after making racist and sexist comments.

Algorithm 121

Algorithm AI AI Computer Science 121

AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. For example, when cataloging financial reports in a document database, extracting and storing the title as a catalog index enables easy retrieval.

AI 105

AI AI Database AWS 105

AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 76

ML ML Deep Learning Deep Learning 76

AWS Machine Learning Blog

MARCH 28, 2024

News CommonCrawl is a dataset released by CommonCrawl in 2016. SEC filings are available online through the SEC’s EDGAR (Electronic Data Gathering, Analysis, and Retrieval) database, which provides open data access. News CommonCrawl SEC Filing Coverage 2016-2022 1993-2022 Size 25.8 the SEC assigned identifier). billion words 5.1

AWS 116

AWS Machine Learning Machine Learning Data Quality 116

Mlearning.ai

JUNE 16, 2023

ML practitioners, believing they had to match the sheer size of ImageNet, refrained from pre-training with much smaller available medical image datasets, let alone developing new ones. December 10, 2016. ImageNet: A Large-Scale Hierarchical Image Database.” link] [3] He, Kaiming, Ross Girshick, and Piotr Dollár. April 14, 2015.

AI 52

AI AI ML ML 52

AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 52

ML ML Deep Learning Deep Learning 52

Mlearning.ai

MARCH 22, 2023

[link] was a great tool to look for other library IDs; to search for library IDs click on Filter menu (do not check Hireable) — Filters — Manifest filters (check Interlocked) — click on Libraries (it looks like the database/hamburger symbol with 3 stacked circles) — click on the library that you want (like OAuth2, OAuth1, Cheerio, etc).

Data Scientist 52

Data Scientist Azure Python Analytics 52

DrivenData Labs

MARCH 30, 2023

His interests are in privacy-preserving machine learning, particularly in the areas of differential privacy, ML security, and federated learning. Qin joined ZS in 2016, where he has been focusing on helping clients realize the value of their RWD and AI investment in R&D through our strategy, data science, and technology capabilities.

Machine Learning 162

Machine Learning Machine Learning Data Science Algorithm 162

Mlearning.ai

SEPTEMBER 4, 2023

information stored in task-specific databases) into generated responses.[34] 37] Amazon might also introduce a vector database service. There is a third way to improve performance in addition to training a foundational model from scratch or fine-tuning a model with specialized language. 34] See note below.[35] 32] Alex Wang, et al.

AI 52

AI AI Azure Machine Learning 52

DrivenData Labs

SEPTEMBER 10, 2024

Many teams combined technical skills in AI/ML with domain knowledge in neuroscience, aging, or healthcare. The dataset includes time-stamped diagnostic and procedural codes for 21,374 patients from a national database, as well as 187 African-American patients from the University of Chicago Medical Center.

Machine Learning 147

Machine Learning Machine Learning Computer Science Computer Science 147

ML Review

MAY 3, 2018

2016) — “ LipNet: End-to-End Sentence-level Lipreading.” [17] Source : Brueckner (2016) [28] By predicting the alphabet characters and an additional “_” (space) character, it’s possible to generate a word prediction by removing repeated letters and empty spaces, as can be seen in fig. 5 for the classification of the word “please”.

Deep Learning 52

Deep Learning Deep Learning Natural Language Processing Machine Learning 52

AWS Machine Learning Blog

DECEMBER 4, 2024

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. Prompt 2: Were there any major world events in 2016 affecting the sale of Vegetables?

AWS 100

AWS AI AI SQL 100

Tableau

DECEMBER 1, 2021

Adam Selipsky becoming CEO in 2016. Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first EOM contract with the database company Hyperion—that’s when I was hired.

Tableau 145

Tableau ML ML Database 145

Tableau

DECEMBER 1, 2021

Adam Selipsky becoming CEO in 2016. Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first OEM contract with the database company Hyperion—that’s when I was hired.

Tableau 98

Tableau ML ML Database 98

The MLOps Blog

JANUARY 26, 2024

TL;DR Feedback integration is crucial for ML models to meet user needs. A robust ML infrastructure gives teams a competitive advantage. I started my ML journey as an analyst back in 2016. Mailchimp’s ML Platform: genesis, challenges, and objectives Mailchimp is a 20-year-old bootstrapped email marketing company.

ML 64

ML ML Data Scientist Machine Learning 64

Mlearning.ai

FEBRUARY 10, 2023

Back in 2016 I was trying to explain to software engineers how to think about machine learning models from a software design perspective; I told them that they should think of a database. Photo by Tobias Fischer on Unsplash What are databases used for? How are neural networks like databases?

Database 52

Database Data Warehouse Machine Learning Machine Learning 52