High school students helped an AI learn to read old handwritten texts

#artificialintelligence

In Italy, 120 high school students helped solve a centuries-old problem: how to give researchers access to the Vatican Secret Archives, a massive collection of documents detailing the Vatican's activities as far back as the eighth century. That should look pretty great on their college applications. The shelves of the Vatican Secret Archives are about 85 kilometers (53 miles) long and house 35,000 volumes of catalogues. But the documents that researchers have scanned and uploaded take up less than an inch. That's because the Vatican seems to not have wanted to share the information.


Supporting Feedback and Assessment of Digital Ink Answers to In-Class Exercises

AAAI Conferences

Effective teaching involves treating the presentation of new material and the assessment of students' mastery of this material as part of a seamless and continuous feedback cycle. We have developed a computer system, called Classroom Learning Partner (CLP), that supports this methodology, and we have used it in teaching an introductory computer science course at MIT over the past year. Through evaluation of controlled classroom experiments, we have demonstrated that this approach reaches students who would have otherwise been left behind, and that it leads to greater attentiveness in class, greater student satisfaction, and better interactions between the instructor and student. The current CLP system consists of a network of Tablet PCs, and software for posing questions to students, interpreting their handwritten answers, and aggregating those answers into equivalence classes, each of which represents a particular level of understanding or misconception of the material. The current system supports a useful set of recognizers for specific types of answers, and employs AI techniques in the knowledge representation and reasoning necessary to support interpretation and aggregation of digital ink answers.


Introduction to Machine Learning & Face Detection in Python

@machinelearnbot

This course is about the fundamental concepts of machine learning, focusing on neural networks, SVM and decision trees. These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example or we may construct algorithms that can have a very very good guess about stock prices movement in the market. In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. The first chapter is about regression: very easy yet very powerful and widely used machine learning technique.


Introduction to Machine Learning & Face Detection in Python

#artificialintelligence

This course is about the fundamental concepts of machine learning, focusing on neural networks, SVM and decision trees. These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example or we may construct algorithms that can have a very very good guess about stock prices movement in the market. In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. The first chapter is about regression: very easy yet very powerful and widely used machine learning technique.


Introduction to Machine Learning & Face Detection in Python

@machinelearnbot

This course is about the fundamental concepts of machine learning, focusing on neural networks, SVM and decision trees. These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example or we may construct algorithms that can have a very very good guess about stock prices movement in the market. In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. The first chapter is about regression: very easy yet very powerful and widely used machine learning technique.