issue

[faisalshaik78]

const apiKey = 'YOUR_API_KEY_HERE'; // Replace with your OpenWeatherMap API key
const searchBtn = document.getElementById('search-btn');
const cityInput = document.getElementById('city-input');
const weatherInfo = document.getElementById('weather-info');

searchBtn.addEventListener('click', () => {
const city = cityInput.value;
if (city) {
fetch(https://api.openweathermap.org/data/2.5/weather?q=${city}&appid=${apiKey}&units=metric)
.then(response => response.json())
.then(data => {
if (data.cod === 200) {
weatherInfo.innerHTML = <h2>${data.name}, ${data.sys.country}</h2> <p>Temperature: ${data.main.temp}°C</p> <p>Weather: ${data.weather[0].description}</p> <p>Humidity: ${data.main.humidity}%</p>;
} else {
weatherInfo.innerHTML = '

City not found. Try again.

';
}
})
.catch(error => console.error('Error:', error));
}
});

[faisalshaik78]

import tensorflow as tf
from tensorflow import keras

Load dataset (e.g., MNIST for digit recognition)

(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

Build model

model = keras.Sequential([
keras.layers.Flatten(input_shape=(28, 28)),
keras.layers.Dense(128, activation='relu'),
keras.layers.Dense(10, activation='softmax')
])

Compile and train

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=5)

Evaluate

model.evaluate(x_test, y_test)