• Stars
    star
    4
  • Rank 3,304,323 (Top 66 %)
  • Language
    Python
  • Created almost 4 years ago
  • Updated over 3 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Automatically send Linkedin invites with personalized messages to a database of targeted profiles.

More Repositories

1

data-engineer-roadmap

Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups
901
star
2

data-science-roadmap

Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups
623
star
3

Linkedin-profiles-scraping

Automatically scrape the web data of people profiles on Linkedin based on a specific search query
Jupyter Notebook
59
star
4

Sales-Reporting

Conduct a Report and Analysis on 200,000 sales data points to answer revenue-related questions for the business
Jupyter Notebook
21
star
5

presidential-debates-comments-clustering

At the point when we started this project, election week is coming up. There was so much excitement in the air on who is the next US president to be elected. There were thousands of articles on who's leading the polls. The US election has been trending on most, if not all, social media platforms. Being Data scientists, we wonder if it would be possible to leverage on these different data sources to understand various topics of discussion surrounding each candidate. Of which, we have decided to focus on Youtube comments as a starting point for this project.
Jupyter Notebook
13
star
6

deeplearning-roadmap

Deep Learning path with multiple notebooks
Jupyter Notebook
5
star
7

data-project-guideline-from-Netflix

"Data science is such a nebulous term. To some, it means data analytics; to some it is synonymous to machine learning; others think there is a data engineering flavor to it. The wide spectrum of possible responsibilities and the nuanced differences across companies or even teams within the same company make the identity evasive. You literally have to speak to a data scientist in company X to understand how company X sees data science. This guidline is inspired by a Netflix talk with a focus on the structure of a data science projects."
5
star
8

flownote-dockers

Python
3
star
9

boringppl-meeting-summarization

Jupyter Notebook
3
star
10

k8s-gateway

JavaScript
2
star
11

Crash-Course-on-Python

A comprehensive curriculum of Python programming foundation
Python
1
star
12

hasbrain-helper-files

Helper files for hasBrain notebooks
Python
1
star
13

Rename-and-Organize-files-directories

Toy problem: Practice generating fake data; then, rename and organize the data into folders of their genres
Python
1
star
14

onboarding

JavaScript
1
star