This is a series of articles that evaluate a question from four perspectives: "Do I need AI for my business? Can I use AI?"
data
Prepare your data for modeling: feature engineering, feature selection, dimensionality reduction (Part 2)
Machine learning algorithms also fail to produce expected results on large amounts of unwanted miscellaneous data. So let's dive into all the options for optimizing your data.
Data preparation for modeling: feature engineering, feature selection, dimensionality reduction (Part 1)
Machine learning algorithms also fail to produce expected results on large amounts of unwanted miscellaneous data. So let's dive into all the options for optimizing your data.
Should I use artificial intelligence in my business? What you need to evaluate before introducing AI (2)
This is a series of articles to evaluate a question from various perspectives: "Do I need AI for my business? Can I use AI?" This issue evaluates the perspective-data.
How AI Product Managers Create Data Strategies for Machine Learning
Enabling machine learning (ML) products has an ongoing collection, cleansing and analysis of data loops for input into ML models. This repetitive loop is the driving force behind the ML algorithm and enables ML products to provide useful insights for users.
1000 times faster! Berkeley proposes a new data enhancement strategy training method to better and faster expand data
Researchers from Berkeley have proposed PBA (Population Based Augmentation) methods to obtain more effective data enhancement strategies and achieve 1000x acceleration with the same effect.
Six steps of data collection, lay the foundation of machine learning model
The time it takes to reduce data preparation becomes more and more important, allowing more time for model testing, debugging, and optimization to create greater value.
How small i robots collect data and process data
How does a small i robot accumulate data? What happens after data collection?