The attempt is to forecast or predict the upcoming value of one stock, activity known as Stock Market Prediction. It is an area that has driven the focus of many individuals including not only companies, but also traders, market participants, data analysts, and even computer engineers working in the domain of Machine Learning (ML) and Artificial Intelligence (AI). Investing funds in the market is subjected to various market risks, as the value of the shares of the company is highly dependent upon the profits and performance of the organization in the marketplace and can thus vary due to various factors such as government policies, microeconomic indicators, demand and supply etc. These variations in the market are studied to develop software and programs using various techniques such as ML, Deep Learning, Neural Networks, AI. Such systems and software can enable the investor to properly anticipate the situation of the company, on the basis of past and present data, the current condition in the market, etc. and give them a direction to make decisions so that they don’t lose their valuable money and earn maximum profits. Machine learning can be defined as the data which is obtained by knowledge extraction. Machines dont have to be programmed explicitly instead they are trained to make decisions that are driven by data. Instead of writing a code for every specific problem, data is provided to the generic algorithms and logic is developed on the basis of that data. When a machine improves its performance based on its past experiences it can be said that machine has truly learnt. The technique for most accurate prediction is by learning from past instances, and to make a program to do this is best possible with machine learning techniques
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Project of Deep Learning_M2QF_University of Paris Saclay [http://www.math-evry.cnrs.fr/departement/doku.php?id=formation:master:m2if]
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Project of Deep Learning_M2QF_University of Paris Saclay [http://www.math-evry.cnrs.fr/departement/doku.php?id=formation:master:m2if]
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