diff --git a/content/learning-paths/cross-platform/multiplying-matrices-with-sme2/_review.md b/content/learning-paths/cross-platform/multiplying-matrices-with-sme2/_review.md deleted file mode 100644 index 49682188ae..0000000000 --- a/content/learning-paths/cross-platform/multiplying-matrices-with-sme2/_review.md +++ /dev/null @@ -1,45 +0,0 @@ ---- -review: - - questions: - question: > - How does SME2 accelerate matrix multiplication? - answers: - - The matrix multiplication operation is a sum of outer products. - - Quantum physics. - correct_answer: 1 - explanation: > - The matrix multiplication operation can be expressed as a sum of outer products, - which allows the SME engine to perform many multiplications at once. - - - questions: - question: > - Why is the ZA storage so important for SME2? - answers: - - It is infinite. - - It holds a 2D view of matrices. - correct_answer: 2 - explanation: > - The ZA storage offers a 2D view of part of a matrix, which is also known as a tile. SME can operate - on complete tiles, or on horizontal or vertical slices of the tiles, which is a useful - and often-used feature in numerous algorithms. ZA storage is finite and has the size SVL x SVL. - - - questions: - question: > - What are predicates? - answers: - - Parts of a sentence or clause containing a verb and stating something about the subject. - - Predicates select the active lanes in a vector operation. - - Predicates are another word for flags from the Processor Status Register (PSR). - correct_answer: 2 - explanation: > - SVE is a predicate-centric architecture. Predicates allow Vector Length Agnosticism (VLA), they support complex nested conditions and loops and reduce vector loop management overhead by allowing lane predication in vector operations. Predicates have their own dedicated registers. - - - -# ================================================================================ -# FIXED, DO NOT MODIFY -# ================================================================================ -title: "Review" # Always the same title -weight: 20 # Set to always be larger than the content in this path -layout: "learningpathall" # All files under learning paths have this same wrapper ---- diff --git a/content/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/_index.md b/content/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/_index.md index f244dab30e..d323fc0bf3 100644 --- a/content/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/_index.md +++ b/content/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/_index.md @@ -1,10 +1,6 @@ --- title: Introduction to TinyML on Arm using PyTorch and ExecuTorch -draft: true -cascade: - draft: true - minutes_to_complete: 40 who_is_this_for: This is an introductory topic for developers and data scientists new to Tiny Machine Learning (TinyML) who want to explore its potential using PyTorch and ExecuTorch. diff --git a/content/learning-paths/mobile-graphics-and-gaming/android_opencv_kleidicv/_review.md b/content/learning-paths/mobile-graphics-and-gaming/android_opencv_kleidicv/_review.md deleted file mode 100644 index 34de98efff..0000000000 --- a/content/learning-paths/mobile-graphics-and-gaming/android_opencv_kleidicv/_review.md +++ /dev/null @@ -1,64 +0,0 @@ ---- -# ================================================================================ -# Edit -# ================================================================================ - -# Always 3 questions. Should try to test the reader's knowledge, and reinforce the key points you want them to remember. - # question: A one sentence question - # answers: The correct answers (from 2-4 answer options only). Should be surrounded by quotes. - # correct_answer: An integer indicating what answer is correct (index starts from 0) - # explanation: A short (1-3 sentence) explanation of why the correct answer is correct. Can add additional context if desired - - -review: - - questions: - question: > - What is the purpose of the `ImageProcessor` class? - answers: - - "To handle user interactions for the application." - - "To apply a selected image processing operation to a Mat object." - - "To manage and display performance metrics for image processing." - correct_answer: 2 - explanation: > - The `ImageProcessor` class is responsible for applying a specified image processing operation from the `ImageOperation` enum to a Mat object. - - - questions: - question: > - How does the `PerformanceMetrics` class compute the standard deviation of operation durations? - answers: - - "By finding the difference between the maximum and minimum durations." - - "By calculating the square root of the average of squared differences from the mean." - - "By dividing the total duration by the number of repetitions." - correct_answer: 2 - explanation: > - The `PerformanceMetrics` class computes the standard deviation by finding the mean of durations, calculating the squared differences from the mean, averaging these values, and taking the square root of the result. - - - questions: - question: > - What is the purpose of the `REPETITIONS` constant in `MainActivity`? - answers: - - "To set the number of times the user can retry loading an image." - - "To determine how many times an image operation is repeated for performance measurement." - - "To limit the maximum number of image processing operations the app supports." - correct_answer: 2 - explanation: > - The `REPETITIONS` constant specifies how many times an image operation is repeated to measure performance and gather statistical data. - - - questions: - question: > - What does the `convertBitmapToMat` method in `MainActivity` achieve? - answers: - - "It initializes OpenCV with the provided bitmap." - - "It converts a Bitmap object into a Mat object and prepares it for processing by changing its color space." - - "It displays the bitmap on the screen." - correct_answer: 2 - explanation: > - The `convertBitmapToMat` method converts a Bitmap to a Mat object using OpenCV utilities and changes its color space from RGBA to BGR, making it ready for further image processing. - -# ================================================================================ -# FIXED, DO NOT MODIFY -# ================================================================================ -title: "Review" # Always the same title -weight: 20 # Set to always be larger than the content in this path -layout: "learningpathall" # All files under learning paths have this same wrapper ---- diff --git a/content/learning-paths/servers-and-cloud-computing/copilot-extension-deployment/_index.md b/content/learning-paths/servers-and-cloud-computing/copilot-extension-deployment/_index.md index 930373ef71..ec477120f8 100644 --- a/content/learning-paths/servers-and-cloud-computing/copilot-extension-deployment/_index.md +++ b/content/learning-paths/servers-and-cloud-computing/copilot-extension-deployment/_index.md @@ -1,6 +1,10 @@ --- title: Graviton Infrastructure for GitHub Copilot Extensions +draft: true +cascade: + draft: true + minutes_to_complete: 30 who_is_this_for: This is an advanced topic for software developers who want to learn how to deploy all necessary infrastructure on AWS for a GitHub Copilot Extension.