Mining and Analyzing LinkedIn Data

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Free download — Mining and Analyzing LinkedIn Data

LinkedIn is a social network focused on professional experience in order to generate connections and relationships between professionals from different areas. Professionals can provide profissional skills and search for jobs by connecting with people around the world. For example, if you would like to work with Data Science you can connect with companies and people who work in this field, increasing your chances of getting a job. On the other hand, companies are able to search for candidates according to the curriculum and skills provided by users. In 2017, LinkedIn established itself as the largest business platform and an important strat tool for both professionals and companies.
It is important that professionals know how to use the data of this social network in their favor. LinkedIn provides some datasets related to your profile, in which it is possible to apply Data Science and Analysis techniques to extract important and interesting insights about our network of connections. We can answer questions like this: What are the main positions of the people who are connected to us Which companies are sending invitations to our profile What is the location of our contacts Is our LinkedIn network made up of people and companies related to our job Are the companies I want to work for sending invitations to my profile These and other questions can be answered during this course, so you can analyze if your network is in line with what you want professionally. Below you can see the main topics that will be implemented step by step
Extract data from your LinkedIn profile using the LinkedIn API and .csv files. If you do not have LinkedIn, you will be able to follow the course using the data about my profile
Extract and analyze connections between users, invitations and text messages
Generate fake data to mask real information
Explore and visualize data related to your contacts’ companies and job titles
Use Levenshtein distance, n-gram similarity and Jaccard distance to measure similarity between strings
Cluster contacts based on similarity between positions, as well as generate HTML views to improve data presentation
Use location APIs to extract latitude and loude of contacts to capture the city and country they live
View the location of contacts dynamically with Google Earth and the Basemap library

File Name:Mining and Analyzing LinkedIn Data
Content Source:N/A
Genre / Category:FREE COURSE
File Size :2GB
Updated and Published:January 26, 2022

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Mining_and_Analyzing.part1.rar – 1024.0 MB
Mining_and_Analyzing.part2.rar – 1024.0 MB
Mining_and_Analyzing.part3.rar – 299.2 MB

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