klotz: machine learning*

"Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

https://en.wikipedia.org/wiki/Machine_learning

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  1. • This is an MCU-based vision AI module powered by Arm Cortex-M55 and Ethos-U55, supporting TensorFlow and PyTorch frameworks.
    • It has a standard CSI interface, onboard digital microphone, and SD card slot.
    • Compatible with XIAO series, Arduino, Raspberry Pi, and ESP dev board.
    • Supports off-the-shelf and custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8.
    • Can be used for industrial automation, smart cities, transportation, smart agriculture, and mobile IoT devices.
  2. A simple and fast data pipeline foundation with sophisticated functionality.
    2024-05-08 Tags: , , , by klotz
  3. • A beginner's guide to understanding Hugging Face Transformers, a library that provides access to thousands of pre-trained transformer models for natural language processing, computer vision, and more.
    • The guide covers the basics of Hugging Face Transformers, including what it is, how it works, and how to use it with a simple example of running Microsoft's Phi-2 LLM in a notebook
    • The guide is designed for non-technical individuals who want to understand open-source machine learning without prior knowledge of Python or machine learning.
  4. This article discusses cyclical encoding as an alternative to one-hot encoding for time series features in machine learning. Cyclical encoding provides the same information to the model with significantly fewer features.
  5. emlearn is an open-source machine learning inference engine designed for microcontrollers and embedded devices. It supports various machine learning models for classification, regression, unsupervised learning, and feature extraction. The engine is portable, with a single header file include, and uses C99 code and static memory allocation. Users can train models in Python and convert them to C code for inference.
  6. Learn how to build an efficient pipeline with Hydra and MLflow
  7. This article explains permutation feature importance (PFI), a popular method for understanding feature importance in explainable AI. The author walks through calculating PFI from scratch using Python and XGBoost, discussing the rationale behind the method and its limitations.
  8. This article provides an introduction to Mlflow, an open-source platform for end-to-end machine learning lifecycle management. The article focuses on using MLflow as an orchestrator for machine learning pipelines, explaining the importance of managing complex pipelines in machine learning projects.
  9. This article discusses TinyLlama, an open-source project for a smaller language model with around 1.1B parameters, capable of complex tasks with less memory usage. The article covers implementation, testing, and performance analysis.
    2024-04-21 Tags: , , by klotz

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