Language: English | Size: 2.29 GB | Duration: 6h 18m
Apply Data Science and Artificial Intelligence techniques to extract and analyze your LinkedIn network
What you'll learn
Extract data from your LinkedIn profile using the LinkedIn API and .csv files
Extract and analyze the connections between users, invitations, and text messages
Generate fake usernames to mask real information
Explore and view data related to your contacts' companies and job titles
Use edit 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 longitude of contacts, in order to capture the city and country of lives
View the location of contacts dynamically with Google Earth and the Basemap library
Cluster contacts using the k-means algorithm
Apply natural language processing techniques to analyze your LinkedIn text messages
Generate word cloud to view the most frequent terms
Extract name entities from text messages
Create a sentiment classifier to extract the polarity of the LinkedIn text messages
Requirements
Programming logic
Basic Python programming
No LinkedIn knowledge is necessary
Description
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 strategic tool for both professionals and companies.
If You Need More Stuff, kindly Visit and Support Us -->> https://CourseWikia.com
Get More Tutorials and Support Us -->> https://FreeCourseWeb.com
We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...