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AI 009
Supervised Learning
A machine learning task of inferring a function from labeled training data.
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Related Knowledge
Data Mining
Data Model
Native App
Recommendation
Task Analysis
Error Analysis
At Uber, event forecasting enables us to future-proof our services based on anticipated user demand. The goal is to accurately predict where, when, and how many ride requests Uber will receive at any given time.
Engineering Extreme Event Forecasting at Uber with Recurrent Neural Networks
eng.uber.com
Data Model
Neural Network
Supervised Learning
highlighted by
Aki Yu
Developer
The first thing I tried was using an optical character recognition library called SwiftOCR. The problem with using SwiftOCR for my use case was that it is designed for reading strings (like giftcard codes) rather than individual numbers. I also couldn’t get it to differentiate between “this is an empty square” and “I couldn’t read this digit”.
Behind the Magic: How we built the ARKit Sudoku Solver
blog.prototypr.io
Supervised Learning
Data Model
Unsupervised Learning
highlighted by
Kevin Hon Chi Hang
Founder of Alphabag
I am providing a high level understanding about various machine learning algorithms along with R & Python codes to run them. These should be sufficient to get your hands dirty.
Essentials of Machine Learning Algorithms (with Python and R Codes)
analyticsvidhya.com
Machine Learning
Supervised Learning
Unsupervised Learning
highlighted by
Aki Yu
Developer
Related Knowledge
RA 022
Data Mining
The practice of examining large pre-existing databases to generate new information.
AI 008
Data Model
Define how data is connected to each other and how they are processed and stored inside the system.
AD 005
Native App
A native app is an application program that developed for use on a particular platform or device.
UX 030
Recommendation
Advice users on the next step or the next content to view.
RA 019
Task Analysis
To identify and understand the activities to be performed by users when interacting with a website or app.
RA 020
Error Analysis
A part of task analysis that identifies the frequency and type of errors that occur for each specified set of task flows.