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Receitas Vó Elisa

website·Indexed 30 days ago

https://ltmleo.github.io/blog

A collection of sweet and savory recipes from Vó Elisa, including dishes such as Bobó de Camarão, Virado à Paulista, various cakes, puddings, and traditional Brazilian savory snacks.

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What's inside Receitas Vó Elisa

  1. Overview of the book 'Humanidade' by Rutger Bregman

    The book 'Humanidade' (2021) by Rutger Bregman challenges the long-held belief that humans are inherently selfish, aggressive, and competitive. Bregman argues that humans are 'programmed' for kindness, cooperation, and trust, suggesting that these traits have an evolutionary basis dating back to the early Homo sapiens. He posits that the shift toward agriculture, property, and competition—rather than innate nature—introduced societal conflict. The central thesis is that most people are fundamentally decent, and believing in human altruism is a realistic posture that can form the basis for genuine societal change.

  2. Overview of the book 'O Segredo Final'

    Written by Dan Brown and published in 2025, 'O Segredo Final' follows Robert Langdon, a professor of Symbology, in Prague. The plot centers on Katherine Solomon, a scientist about to publish a revolutionary book on human consciousness and noetic science. After a brutal murder and Katherine's disappearance, Langdon is pursued by a powerful organization and a mythological adversary from Prague's history, leading him through a journey involving futuristic science and mystical traditions across Prague, London, and New York.

  4. Overview of OCI AI Model Catalog

    The OCI AI Model Catalog is a centralized repository providing a variety of pre-trained and custom AI models. It allows developers to discover, access, and deploy AI capabilities into their applications via APIs and SDKs. Key features include support for Natural Language Processing (NLP), Computer Vision, and Speech Recognition, as well as the ability to fine-tune pre-trained models with proprietary data to improve accuracy and relevance.

  5. Overview of OCI Vision capabilities

    OCI Vision is a pre-trained AI service from Oracle Cloud Infrastructure used to analyze images and videos to extract useful information. It is designed for integration into enterprise applications without requiring advanced Machine Learning expertise. Key capabilities include:

    • Image Classification: Identifies categories or labels in images (e.g., e-commerce product classification).
    • Object Detection: Locates and identifies specific objects within images (e.g., counting vehicles in traffic).
    • Optical Character Recognition (OCR): Extracts text from images or scanned documents (e.g., processing invoices or ID cards).
    • Table Extraction: Identifies and extracts structured tables from documents (e.g., financial tables in reports).
    • Key-Value Extraction: Identifies key-value pairs in documents (e.g., extracting "Name: John Doe" from forms).
    • Document Classification: Categorizes documents into specific types (e.g., distinguishing between an invoice, contract, or report).
    • Video Analysis: Processes video to detect objects, actions, or events (e.g., real-time security monitoring).
    • Model Customization: Allows fine-tuning of pre-trained models using customer-specific data (e.g., training a model to recognize specific brand logos).

  6. Overview of Ensemble Learning techniques

    Ensemble learning combines multiple machine learning models to create a more powerful predictive model. While primarily used for supervised learning, it can also be applied to unsupervised models. The three primary types are:

    • Bagging: Uses the same algorithm to train subsets on different datasets in parallel.
    • Boosting: Uses the same algorithm to train subsets on different datasets sequentially.
    • Stacking: Combines predictions from different machine learning algorithms into a final model.

  8. Overview of OCI Speech capabilities

    OCI Speech is a pre-trained AI service from Oracle Cloud Infrastructure designed for high-accuracy speech-to-text transcription. It is intended for integration into enterprise applications and automated workflows, supporting both real-time audio streams and batch processing of audio files.

  9. Overview of Red Hat OpenShift Unified Platform

    Red Hat OpenShift is a unified platform capable of virtualizing both containers and Virtual Machines (VMs). It supports a lifecycle strategy of Maintain -> Migrate -> Modernize. The platform offers four types of subscriptions: OVE, OKE, OCP, and OPP.

  10. Overview of Omelette Au Fromage Podcast Automation

    Omelette Au Fromage is a podcast designed to teach phrases in foreign languages (Dutch, Italian, Spanish, and French) to Portuguese speakers through strategic repetition. The production process uses a 'layered automation' approach, dividing the complex workflow into independent, manageable stages to facilitate maintenance and scalability.

  11. Overview of the OCI AI Portfolio

    The OCI AI Portfolio is a full-stack offering designed to help businesses adopt Artificial Intelligence and Generative AI. It is organized into four pillars:

    1. AI Infrastructure: High-performance compute resources (NVIDIA GPUs, AMD Instinct MI300X) in RDMA clusters for training large ML and Deep Learning models.
    2. ML Services: Platforms for data scientists, including OCI Data Science (JupyterLab, AutoML) and in-database ML (Autonomous Database, HeatWave).
    3. AI Services: Pre-trained APIs for rapid integration, including OCI Generative AI (LLMs from Cohere, Meta Llama, and Oracle with fine-tuning), Vision (OCR, object detection), Language (translation, sentiment analysis), Speech (transcription), and Document Understanding.
    4. AI in Applications: AI features integrated directly into SaaS offerings like Oracle Fusion Applications.

  12. Overview of Generalized Linear Multilevel Models (GLMM)

    Generalized Linear Multilevel Models (GLMM), also referred to as Hierarchical Linear Models (HLM), Mixed Models, or Nested Models, are used to analyze data with a hierarchical structure (e.g., students within schools, patients within hospitals). Unlike standard OLS/GLM, GLMMs account for heteroscedasticity by incorporating random effects for intercepts and slopes.

    Key variance components:

    • var(u_0j): Variance of random intercept effects.
    • var(u_ij): Variance of random slope effects.

    Model types based on variance:

    • OLS (GLM): Both variances are approximately 0.
    • Random Intercepts: var(u_0j) != 0 and var(u_ij) ~= 0.
    • Random Slopes: var(u_0j) ~= 0 and var(u_ij) != 0.
    • Random Intercepts and Slopes: Both variances are non-zero.