Fortaleza, Ceará, Brasil
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I'm Daniel, a tech expert with 25 years of experience in Linux server istration…

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Licencias y certificaciones

Publicaciones

Cursos

  • Ansible in a nutshell - Howto

    2014

  • Background Job in Ruby on Rails - Howto

    2013

  • Improving OO with Ruby - Caelum - (RR-17)

    2012

  • Java Developer - Fap

    2009

  • Java and Object Orientation - Caelum - (FJ-11)

    2010

  • Java for Web Development - Caelum - (FJ-21)

    2010

  • Laboratory tests with Java, XML and Design Patterns - Caelum - (FJ-16)

    2010

  • Organizing JavaScript - Howto

    2015

  • Rails Caching - Howto

    2013

  • Rails Engines - Howto

    2013

  • Ruby on Rails from Beginning to Advanced - Egenial

    2011

  • Security in Ruby on Rails - Howto

    2013

  • Web Development with Rails - Howto

    2012

  • Web programmer - Senac

    2007

  • Workshop BootStrappers

    2012

  • Workshop Startup Dev

    2012

Proyectos

  • JusGPT

    -

    A Python-based RAG application tailored for the legal domain, leveraging Langchain and Pinecone to navigate Brazilian legal texts with OpenAI's GPT-4 API.

  • Reinforcement Learning

    -

    AI is playing Street Fighter.

  • EDA wine reviews

    -

    This project conducted exploratory data analysis using a Wine Review dataset found on Kaggle containing approximately 130k reviews from the Wine Enthusiast to understand better:

    Where does the best wine in the world come from?
    Is price related to quality?
    Are certain varieties of wine of higher quality?
    What is the best wine in each price bracket?
    What words are most used when talking about wine?

  • Time series forecasting in TensorFlow

    -

    This notebook's goal is to familiarize you with working with time series data and TensorFlow.

    ⚠️ This is not financial advice!

    What is a time series problem?
    Time series problems deal with data over time.

    Such as the number of staff in a company over ten years, sales of computers for the past five years, and electricity usage for the past 50 years.

  • Convolutional Neural Networks and Computer Vision with TensorFlow

    -

    In deep learning, many model architectures can be used for different problems. For example, you could use a convolutional neural network to make predictions on image and/or text data. However, in practice, some architectures typically work better than others.

    Workflow
    Getting a dataset to work with
    Architecture of a convolutional neural network
    A quick end-to-end example
    Steps in modeling for binary image classification with CNNs
    Becoming one with the data
    Preparing…

    In deep learning, many model architectures can be used for different problems. For example, you could use a convolutional neural network to make predictions on image and/or text data. However, in practice, some architectures typically work better than others.

    Workflow
    Getting a dataset to work with
    Architecture of a convolutional neural network
    A quick end-to-end example
    Steps in modeling for binary image classification with CNNs
    Becoming one with the data
    Preparing data for modeling
    Creating a CNN model
    Fitting a model
    Evaluating a model
    Improving a model
    Predicting with a trained model
    Contains a little experiment with data augmentation

Idiomas

  • English

    Competencia básica profesional

  • Portuguese

    Competencia bilingüe o nativa

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