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Scraping Website: How to Write a Script in Python

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Here's a python script that you can use as a model to scrape a website. Python script The below logic uses BeautifulSoup Package for web scraping. import requests from bs4 import BeautifulSoup url = 'https://www.example.com' response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') # Print the title of the webpage print(soup.title.text) # Print all the links in the webpage for link in soup.find_all('a'):     print(link.get('href')) In this script, we first import the Requests and Beautiful Soup libraries. We then define the URL we want to scrape and use the Requests library to send a GET request to that URL. We then pass the response text to Beautiful Soup to parse the HTML contents of the webpage. We then use Beautiful Soup to extract the title of the webpage and print it to the console. We also use a for loop to find all the links in the webpage and print their href attributes to the console. This is just a basic example, but

2 Top Python Libraries to Create ML model

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To Create a Model of Machine Learning in Python, you need TWO libraries. One is 'NUMPY' and the other one is 'PANDAS'. 2 Top Libraries You Need To Build a model of Machine learning you need the right kind of data. So, use the data for your project should be refined. Else, it will not produce correct results. The prime steps are Data Analysis and Data Preprocessing. NUMPY - It has the capabilities of Calculations. PANDAS- It has the capabilities of Data processing. How Install Python Machine Learning Libraries  import  NumPy as np # linear algebra import pandas as PD # data processing, CSV file I/O (e.g. PD.read_csv) How to Check NumPy/Pandas installed After '.' you need to give double underscore on both sides of the version.  How Many Types of Data You Need You need two types of data. One is data to build a model and the other one is data you need to test the model. Raw data Evaluate-data How to Build a Model Flowchart I have given a f

Real thoughts on IBM power8 servers to use on analytics

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IBM Servers International Business Machines Corp, in its latest attempt at reviving demand for its hardware products, is launching high-end system servers that it says are 50 times faster than its closest competitor at analysing data.  The POWER8 servers , the product of a $2.4 billion, three-year investment, are part of the company's decade-long shift to higher-value hardware technology.    IBM  said the machines are 50 times faster than the low-end x86-based servers it sold to Chinese PC maker  Lenovo  Group Ltd in January.  The technology services provider said on Wednesday it hopes the servers, designed for large-scale computing, will appeal to clients looking to manage new types of social and mobile computing and mass amounts of data. Last week, the company reported its lowest quarterly revenue in five years, weighed down by falling demand for its storage and server products. IBM dominates the higher-end server market with 57 percent market share, according to res