Ai Assistant we are going to make our own virtual Ai Assistant using Python Language We can let that Assistant do lots of things for us like We can voice command, we can deliver greetings and we can tell the assistant to open applications for us. We have provided lines of code and images for example for you to understand you better. We will use Pycharm IDE as it's easy and convenient to use. Pycharm We will start by importing important libraries import pyttsx3 # pip install pyttsx3 import datetime # It's an prebuilt library import speech_recognition as sr # pip install SpeechRecognition import wikipedia import smtplib import webbrowser as wb import psutil import pyjokes import os import pyautogui import json from urllib.request import urlopen import wolframalpha import time engine = pyttsx3.init() wolframalpha_app_id = '99LHQ4-3LA69J466R' def speak(audio): engine.say(audio) engine.runAndWait() def time_(): Time = datetime.datetime.now().strftime("
Board Game Prediction using Machine Learning 1. Importing Libraries and Loading the Data After the .csv file 'games.csv' has been copied to the current directory, we can import the data as a Pandas DataFrame. As a DataFrame, we will be able to easily explore the type, amount, and distribution of data. Furthermore, using a correlation matrix, we can explore the relationships between parameters. This is an important step in determining the type of machine learning algorithm to utilize. import sys import pandas import matplotlib import seaborn import sklearn # Read in the data. games = pandas.read_csv("games.csv") # Print the names of the columns in games. print(games.columns) print(games.shape) # Make a histogram of all the ratings in the average_rating column. plt.hist(games["average_rating"]) # Show the plot. plt.show() # games[games["average_rating"] == 0] # Print the first row of all the games with zero scores. # The .iloc method on dataframes