GitHub - miachenberkeley/DataProjectStartup

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Name		Name	Last commit message	Last commit date
Latest commit History 25 Commits
.idea		.idea
.ipynb_checkpoints		.ipynb_checkpoints
D3JS		D3JS
DeepLearningTutorials		DeepLearningTutorials
Tutorial		Tutorial
VC_data_scrapping		VC_data_scrapping
code		code
data		data
json_extract/py_VC_Project		json_extract/py_VC_Project
techcrunch data		techcrunch data
venv		venv
.metadata_mia.json.icloud		.metadata_mia.json.icloud
3.uncontr		3.uncontr
README.md		README.md
Task_To_Do.xlsx		Task_To_Do.xlsx
TechCrunch_hand.xlsx		TechCrunch_hand.xlsx
altegrad_1_fev.docx		altegrad_1_fev.docx
data_VC.py		data_VC.py
datacrunch_json_reader.py		datacrunch_json_reader.py
investors-2-2-2017-copie.csv		investors-2-2-2017-copie.csv
investors-2-2-2017.csv		investors-2-2-2017.csv
test.csv		test.csv

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## Synopsis and motivation

The goal of this project is to analyse trends in the creation of startups and
Venture Capital investments in various markets worldwide. Several types of data
shall be used during this project: news articles from Techcrunch and investments
data from Crunchbase. The ambition is to be able to extract powerful market
intelligence to:
• Understand why startups fail
• Know what key differentiations are important for VCs
• Identify markets currently being disrupted & tomorrow’s opportunities
• Map the VC ecosystem with relationships & targeted markets

## Project advancement

A first group of students have already worked on this project during 4 months. They used Anseri as tool to formate data.
Actually, we think that we can use tensorflow as tool to continue the project.

## Installation

- Python
- Librairies : NLTK, Word2Vec, Numpy, iGraph, Anaconda, selenium, TensorFlow
- All tutorials are available in the directory DeepLearningTutorials

## Contributors
This project is mainly developped by students from Polytechnique & Berkeley.

## License

This is a scientific project supervised by Berkeley and Polytechnique.