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Computer Vision: YOLO Custom Object Detection with Colab GPU

#artificialintelligence

Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. This is the fourth course from my Computer Vision series. As you know Object Detection is the most used applications of Computer Vision, in which the computer will be able to recognize and classify objects inside an image. This course is equally divided into two halves.


Computer Vision: YOLO Custom Object Detection with Colab GPU

#artificialintelligence

Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. This is the fourth course from my Computer Vision series. As you know Object Detection is the most used applications of Computer Vision, in which the computer will be able to recognize and classify objects inside an image. This course is equally divided into two halves.


Computer Vision: YOLO Custom Object Detection with Colab GPU

#artificialintelligence

Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. Python based YOLO Object Detection using Pre-trained Dataset Models as well as Custom Trained Dataset Models. This is the fourth course from my Computer Vision series. As you know Object Detection is the most used applications of Computer Vision, in which the computer will be able to recognize and classify objects inside an image. This course is equally divided into two halves.


E-Learning Quizzes with R/exams for Moodle and OpenOLAT

#artificialintelligence

E-learning resources such as online tests and quizzes or more formal e-exams are very useful in a variety of settings: formative vs. summative assessments; in-class vs. distance learning; synchronous vs. asynchronous; small vs. large groups of students. Some typical examples are outlined here. R/exams can support these scenarios by creating a sufficiently large number of randomized versions of dynamic exercises that can subsequently be imported into a learning management system (LMS). The actual quiz/test/exam is then conducted in the LMS only, i.e., without the need to have R running in the background, because all exercises and corresponding solutions have been pre-computed and stored in the LMS. Popular LMS include the open-source systems Moodle, Canvas, OpenOLAT, or Ilias or the commerical Blackboard system.


Some Analysis with Astronomy data (in Python)

@machinelearnbot

The following problems appeared as assignments in the coursera course Data-Driven Astronomy. One of the most widely used formats for astronomical images is the Flexible Image Transport System. In a FITS file, the image is stored in a numerical array. In this assignment, we shall focuss on calculating the mean of a stack of FITS files. Each individual file may or may not have a detected a pulsar, but in the final stack we should be able to see a clear detection.