La pandemia de COVID-19 ha tenido un impacto significativo en la economía mundial. Muchos países experimentaron fuertes caídas en el PIB y aumentos en el desempleo debido a los cierres generalizados y las restricciones a los viajes. Aunque las vacunas ofrecen esperanza de una recuperación económica en 2021, el panorama a corto plazo sigue siendo incierto dado el resurgimiento de casos en algunas partes del mundo.
China Crowdfinding Berlin School Pres 21052015Conor Roche
Crowdfunding in China has grown rapidly across various models from 2014 to 2015. Equity crowdfunding regulations were introduced in late 2014, though they primarily allow accredited investors. Reward and donation crowdfunding have been most active, funding business, social causes, and arts projects. The Chinese government aims to encourage entrepreneurship and creative industries through crowdfunding. While still developing, crowdfunding presents opportunities to raise film financing within China and for Chinese-international co-productions. The industry is expected to continue expanding as platforms consolidate and regulations evolve further.
This document discusses using Bayesian analysis and probabilistic modeling to build a classifier that predicts housing prices based on location using data from Craigslist postings. It trains a model using Gaussian and box car distributions over price likelihoods and priors to determine the probability of a given price at a location based on keywords in listings, and tools used include analyzing posts regarding roommates, amenities, parking, and kitchen details. The author is a physics PhD from UCLA researching phase retrieval from incomplete noisy data.
Craigslist ++ is a project that aims to improve access to Craigslist housing information and provide insights into new locations. It uses a classifier and Bayesian analysis to predict housing prices based on listings data. The classifier categorizes listings by attributes like price, location, amenities, and whether they are spam. Bayesian price prediction models the probability of a price given a location using a likelihood function based on a Gaussian distribution and a prior box car distribution. This provides a quicker way to find housing options at a given price point and gives insights into pricing trends for different areas.