Mohit Sharma (@imoisharma)
github

imoisharma

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Top repositories

1

Python-Web-Scraping-

When performing data science tasks, it's common to want to use data found on the internet. You'll usually be able to access this data in csv format, or via an Application Programming Interface (API). However, there are times when the data you want can only be accessed as part of a web page. In cases like this, you'll want to use a technique called web scraping to get the data from the web page into a format you can work with in your analysis.
Jupyter Notebook
22
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2

Text--Summarization

Automatic summarization is the process of shortening a text document with software, in order to create a summary with the major points of the original document. Technologies that can make a coherent summary take into account variables such as length, writing style and syntax.
Python
15
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3

aws-scripts

AWS Shell Scripts for most of the AWS Services. Any issues contact via [email protected]
Shell
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4

U.S.-Patents-Claims

I am using USPTO ( United States Patent and Trademark Office) SOURCE LINK WHICH is the federal agency for granting U.S. patents and registering trademarks. They also provide open data about U.S. patents. So, today we will work with one open dataset they provided on their website. (Source- download the dataset from here-Patent grant full-text data/XML) Dataset Description - Patent grant full-text data (no images) (JAN 1976 - present) (1976–2001 Automated Patent System (APS) format is Green Book) Contains the full text of each patent grant issued weekly (Tuesdays) from January 1, 1976, to present (excludes images/drawings and reexaminations). The dataset contains (JAN 2002 - present) the full text of each patent grant issued weekly (Tuesdays) (excludes images/drawings and reexaminations). The file format is eXtensible Markup Language (XML) in accordance with the Patent Grant International Common Element (ICE) Document Type Definition (DTD).
Jupyter Notebook
7
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5

aws-codepipeline-s3-codedeploy-linux-2.0

Use this sample when creating a simple pipeline in AWS CodePipeline while following the Simple Pipeline Walkthrough tutorial.
Shell
4
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6

Data-Visualization

Jupyter Notebook
3
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7

Complete-Python-Tutorial

Hello! Welcome to my GitHub Account. Today, I am going to explain each and every single concept of Python.
Jupyter Notebook
3
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8

bash_best_practices

This repository provides some best-practices for writing bash scripts.
2
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9

k8s-workloads

A practical guide created for everyone to learn K8s and build Highly available & scalable environment.
2
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10

infra-public

Go-to destination for all things IAC.
HCL
1
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11

Docker-Sample

This is a workshop which introduces basic Docker concepts - how to use it, why it's important, and where to get more information afterwards. This workshop is designed to be self-running and contains practical and conceptual information inside the repository. This workshop aims to for the comprehension and application of Docker knowledge.
Dockerfile
1
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12

matplotlib-basic

In this Repository I've tried to cover all the basic topics of Matplotlib library. Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
Jupyter Notebook
1
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