… mainstream market for electric vehicles, focusing on mass-market consumers. It uses a …
The survey was analysed using an unsupervised learning algorithm from machine learning …

… The scope for market design goes far beyond the more mainstream application like setting
rules of bidding and reserve prices for auctions or designing tiers of services, and in our view, …

… market and stock market system, stock investment has become one of the main investment
channels for investors. The stock market … of change of the stock market has always been a hot …

… The stock market is very volatile and non-stationary and … machine learning algorithms are
analyzed for stock market … Mainstream traders usually conduct fundamental analysis and …

… Therefore, it is a prevalent method of machine learning. This paper establishes a vector
support mechanismbased model to simulate and forecast stock market trends. Wapnik …

… The term appears increasingly in mainstream media outlets. For example, the professional
body … In the credit market this isn’t just a preference, but enforced through the Fair Credit …

… been incorporated in mainstream machine learning, while other parts of machine learning
have … For decades, scholars working at the intersection of marketing and economics have built …

… is a book for people who want to apply machine learning (ML) to their own real-world
problems. It describes and explains the processes, algorithms, and tools that mainstream ML …

… world agriculture can be constructed as a “learning machine” that leaves room for a variety
of … , processes and actors that were invisible in mainstream models, and asserted a vision of …

… We focus on the application of stock market, however, machine learning and deep learning
methods have been applied in many financial problems. It would be beyond the scope of this …