Course Content

ABSTRACT

 

Film Industry is not only a industry or a centre of entertainment, rather it is now a centre of global business. All over the world is now excited about a movie’s box office success, popularity etc. A huge data is available online about these movies success or popularity. The film industry has always been a very important sector in the global market. Therefore, it is very important to maximize the profit by predicting the movie success before its release. The number of movies produced in the world is growing at an exponential rate and success rate of movie is of utmost importance since billions of dollars are invested in the making of each of these movies. In such a scenario, prior knowledge about the success or failure of a particular movie and what factor affect the movie success will benefit the production houses since these predictions will give them a fair idea of how to go about with the advertising and campaigning, which itself is an expensive affair altogether. So, the prediction of the success of a movie is very essential to the film industry. We proposed to develop a model for predicting the success of movie being a Hit or Flop, long before a movie is actually released using machine learning techniques and algorithms.

INTRODUCTION

Now a day’s movies are not the only source of recreation, rather it is one of the major sources of global commerce and marketing. Movies create a new craze among people especially young people. Not only movie directors and box office officials are concerned with the success of movies but general people also. People used to talk about these in social Medias. Therefore analysis of social media data about movies is recently popular among the data analysts. Other than this there remain some other scopes like analyzing a director’s previous success histories or a actor’s previous popularity etc. Again the analysis may be different on different countries. Naturally peoples from all the regions of the world do not react in the similar way. Movies are now available on internet. There are platforms like IMDB (Internet Movie Database), Rotten Tomatoes, Met critics etc. where people can share their reviews about movies. Movies continue to be a major source of entertainment in any country. However, this industry also incurs a lot of losses when the movie does not perform at the Box Office. Our solution will try to predict the success rate of a movie by doing predictive analysis on the various features of the movie. Day by day these platforms are becoming popular since people are getting honest reviews there. So, huge data is available online about reviews and ratings of movies. So, the prediction of the success of a movie is very essential to the film industry. We proposed to develop a model for predicting the success of movie being a Hit or Flop, long before a movie is actually released using machine learning techniques and algorithms.

BLOCK DIAGRAM

SYSTEM REQUIREMENTS

Hardware Requirement:-

•      System: Pentium IV 2.4 GHz. 

•      Hard Disk: 500 GB.

•      Ram: 4 GB.

•      Any desktop / Laptop system with above configuration or higher level .

 

Software Requirements:-

•      Operating system : Windows XP / 7

•      Coding Language :Python

•      Interpreter             :Python 3.6

•      IDE                       : Python IDE

•      ML APIS              :Sklearn, numpy, pandas, matplotlib, keras, tensorflow, tkinter

•      Algorithms used:  random forest, decision tree, K-means clustering, SVM

Functional Requirements:-

 

·         Capable of predicting success of a movie.

·         Predicts  of success of movie being a Hit or Flop, long before a movie is actually released

 

Non Functional Requirements:-

 

They basically deal with issues like:

•      Security

•      Maintainability

•      Reliability

•      Scalability

•      Performance

CONCLUSION

 

Now a day’s movies are not the only source of recreation, rather it is one of the major sources of global commerce and marketing. Movies create a new craze among people especially young people. Not only movie directors and box office officials are concerned with the success of movies but general people also. The prediction of success of movie with good accuracy is needed in the film industry which helps different people working in the film industry mainly for the investors. We proposed to develop a model for predicting the success of movie being a Hit or Flop, long before a movie is actually released using machine learning techniques and algorithms.