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auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

covid

covid-mask

covid-response-bot

data-science--cheat-sheet

Cheat Sheets

diagrams

github-example

This is just demonstration.

graphql-compose-examples

Live examples of schemas builded with graphql-compose

linux_tweet_app

A very simple webapp based on NGINX

neighborhood_analysis

Coursera Capstone Project is part of final course of IBM Data Science.

regression-in-keras

A. Build a baseline model Use the Keras library to build a neural network with the following: - One hidden layer of 10 nodes, and a ReLU activation function - Use the adam optimizer and the mean squared error as the loss function. 1. Randomly split the data into a training and test sets by holding 30% of the data for testing. You can use the train_test_splithelper function from Scikit-learn. 2. Train the model on the training data using 50 epochs. 3. Evaluate the model on the test data and compute the mean squared error between the predicted concrete strength and the actual concrete strength. You can use the mean_squared_error function from Scikit-learn. 4. Repeat steps 1 - 3, 50 times, i.e., create a list of 50 mean squared errors. 5. Report the mean and the standard deviation of the mean squared errors.

responce_systems

Responce Systems Hackathon 2020