Portal de Periódicos da CAPES

Investing Data with Machine Learning Using Python

2020; Springer Nature; Linguagem: Inglês

10.1007/978-981-15-3647-2_1

2522-5170

Anish Gupta, Manish Gupta, Prateek Chaturvedi,

Stock Market Forecasting Methods

Data can be classified into various forms like structured, semi-structured and unstructured. Data is growing rapidly in exponential form. Not all the data is useful; percentage of useful data is to be identified for future use. From useful data, future is to be predicted by analyzing the past. There are various types of algorithms and tools available in market through which we can predict our future [9]. Through this paper, we shall try to analyze and predict stocks and investing data of various companies such as S&P 500 Index, standard and poor’s 500, Yahoo Finance, Google Finance through supervised and unsupervised machine learning algorithms. Machine learning plays vital role in today’s scenario from self-driven cars, Google Assistance and Siri to news recommendation systems. It has been incorporated into mainstream tools, news recommendation engines, sentiment analysis, stock screeners, etc.