ODSC - Open Data Science

MARCH 22, 2023

This process is entirely automated, and when the same XGBoost model was re-trained on the cleaned data, it achieved 83% accuracy (with zero change to the modeling code). Previously, he was a senior scientist at Amazon Web Services developing AutoML and Deep Learning algorithms that now power ML applications at hundreds of companies.

ML 88

ML ML Data Scientist AI 88

Flipboard

FEBRUARY 2, 2023

The player tracking data contains the player’s position, direction, acceleration, and more (in x,y coordinates). There are around 3,000 and 4,000 plays from four NFL seasons (2018–2021) for punt and kickoff plays, respectively. The data distribution for punt and kickoff are different.

Cross Validation 123

Cross Validation ML ML Machine Learning 123

Mlearning.ai

JANUARY 26, 2023

It can be gradually “enriched” so the typical hierarchy of data is thus: Raw data ↓ Cleaned data ↓ Analysis-ready data ↓ Decision-ready data ↓ Decisions. For example, vector maps of roads of an area coming from different sources is the raw data. 2018, July). Remote Sensing, 12(24), 4033.

AWS 98

AWS Database Data Science Clean Data 98

Flipboard

JULY 10, 2023

By using our mathematical notation, the entire training process of the autoencoder can be written as follows: Figure 2 demonstrates the basic architecture of an autoencoder: Figure 2: Architecture of Autoencoder (inspired by Hubens, “Deep Inside: Autoencoders,” Towards Data Science , 2018 ).

Deep Learning 132

Deep Learning Deep Learning Machine Learning Machine Learning 132

Tableau

JANUARY 27, 2021

We also reached some incredible milestones with Tableau Prep, our easy-to-use, visual, self-service data prep product. In 2020, we added the ability to write to external databases so you can use clean data anywhere. Tableau Prep can now be used across more use cases and directly in the browser.

Tableau 102

Tableau Business Intelligence Business Intelligence Analytics 102

How to Learn Machine Learning

OCTOBER 10, 2024

Real-Life Examples of Poor Training Data in Machine Learning Amazon’s Hiring Algorithm Disaster In 2018, Amazon made headlines for developing an AI-powered hiring tool to screen job applicants. Data Quality Factors to Consider So, how can you avoid these types of failures in your ML projects? Sounds great, right?

Machine Learning 52

Machine Learning Machine Learning Data Quality Algorithm 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. He has collaborated with the Amazon Machine Learning Solutions Lab in providing clean data for them to work with as well as providing domain knowledge about the data itself.

ML 76

ML ML Machine Learning Machine Learning 76