Exercise for extracting valid time and date formats from any text.
Monday, 26 March 2018
Saturday, 17 March 2018
How to use Google for Free Books
In this era, education becomes very much accessible to each and everyone with just simple internet connection. Some people like to use 3G/4G/broadband data for social networking, some use for movies. As per my opinion, we can make best use of internet by downloading the some good books which are uploaded at some point of the world by someone.
Google helps us in finding the books by powerful search engine.
case1: If you want to find a pdf files uploaded on internet, in google search engine type
Mastering Python filetype:pdf
This query will show you all the "pdf" files with name Mastering Python.
In this way we can find a book based on its upload.
case2: Type the following in google search engine
intitle:index.of pdf “Book title”
Google helps us in finding the books by powerful search engine.
case1: If you want to find a pdf files uploaded on internet, in google search engine type
Mastering Python filetype:pdf
This query will show you all the "pdf" files with name Mastering Python.
In this way we can find a book based on its upload.
case2: Type the following in google search engine
intitle:index.of pdf “Book title”
First few results will give you direct access to database directory where you will get books for free and you need to click only once to download them.
You can also download books for a general topic.
e.g. For Quantum Mechanics, type in Google search bar:
intitle:index.of pdf Quantum Mechanics
Have a look at advanced google search operators:
Hadoop- Hive- Map Reuce
Hadoop Hands On
Some examples of Hive Query
Map-Reduce for the NSE data analysis.
Some examples of Hive Query
Map-Reduce for the NSE data analysis.
Linear Regression - Python - Hypothesis Testing
Linear Regression (Statistics)
Dataset = New Car Loans.
We will try to fit the linear mean curve in traditional way.
Also, we will try to fit the non-parametric technique.
Dataset = New Car Loans.
We will try to fit the linear mean curve in traditional way.
Also, we will try to fit the non-parametric technique.
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