Showing 2 open source projects for "temperature"

View related business solutions
  • Ship Agents Faster Icon
    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

    Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
    Get Started Free
  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
    Try Free
  • 1
    Solar Wi-Fi weather station on ESP12

    Solar Wi-Fi weather station on ESP12

    Solar Wi-Fi weather station on ESP12

    #ESP.Meteo: Solar Wi-Fi weather station on ESP12 + ionistor + solar panel Current Functionality: *Forecasting the probability of frosts (according to the methods of Professor Brounov) *Forecast of the height of the lower edge of the cloud (VNGO by Selezneva) *Calculation of the height of the sensor according to the barometric formula (altimeter, for other projects) *Measurement of street temperature *Measurement of outdoor humidity *Measurement of street pressure *Calculation of the dew point *Monitoring of voltage on ionistors (charge-discharge control) *Monitoring the opening of the box flap with potatoes *Monitoring the system time-out every 5 minutes (operating time ~ 480 ms) *Monitoring the temperature on the balcony (the ability to connect up to 16 sensors DS18B20: 2 groups of 8 sensors per two APIKEY) *Sending data to the Thingspeak cloud *Sending data to Twitter
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    char-rnn

    char-rnn

    Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN)

    ...It is straightforward: you provide a single text file, train the model to minimize next-character prediction loss, then sample from the trained network to generate new text one character at a time in the style of the dataset. The project is designed for experimentation, offering tunable settings for depth, hidden size, dropout, sequence length, and sampling temperature to control creativity and coherence. It is frequently used as a learning project for understanding sequence modeling, recurrent training dynamics, and the practical details of text generation.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next