Helm configuration to deploy airflow in Kubernetes with production level using the minimun resources. (Demo)

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A rational investor, only take desitions based on objective information.

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ETL to handle data from the goberment public API's and websites to our own database to create the reports, every steps code inside a function and every task was coded in side a Django command mangger.

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Django server created to retrieve forecast data using live demo data, to forecast the amount of sellings of the products in a store.

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We will create a map from the reality and put a diferential robot in there with the aim to use an path planning algorith through reinforecement learning (PPO)

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Notebooks where i analysis birds sound as a part of my data science challenge, the dataset consist of the audio of the birds in the nature. I create a custom model with CNN and LSTM neural networks to classify to which kind of bird the audio belongs.

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Transfer learning using eficientNet + xception and aumentation tecniques to clasify the leafs of cassava.

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I've created a simple explination to undestand machine learning, focusing on neural networks, from the perceptron to a multi-layer neural network application.

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I've created a simple PID control system with an incremental encoder and an ESP8266 microcontroller. Python to extract sample data from the motor behavior and Matlab to system modeling.

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This tutorial shows how to configure an ESP32 in conjunction with the Node-Red framework of IBM, generating an IoT application ready for production.

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