Sales Prediction using machine learning
In today’s world Artificial intelligence has taken over the world and it has become an important part of human’s life. We can see it everywhere now in our mobile phones, computers. New invention in technologies are mainly based on artificial intelligence as it’s the future. It’s an hot topic many people are talking about it as it has many features of it. Machine learning is an application of artificial intelligence which provides systems the ability to automatically learn and improve the data without been programmed for it. The way toward learning starts with perceptions or information, for example, models, direct understanding, or guidance, so as to search for designs in information and settle on better choices later on dependent on the models that we give. The essential point is to permit the PCs adapt naturally without human intercession or help and change activities in like manner. The use of artificial intelligence is been increasing day by day. There are many sectors where machine learning is been used in healthcare, technology, defence, government, business.
Machine learning in business helps in enhancing business scalability and improving business operations for companies across the globe. The idea of the project is to help the growing businesses and the small business to grow as in this project the user can use their historical data of a certain product to predict the future sales of the certain product which will help them to grow. There are already existing business which use this technology in order to help them in business.

Potential Users
The potential of this service can be anybody who owns a business or who wants to open a business or who provide a certain type of service. People owning business on small sector will be one of the main potential clients as they usually don’t know the demand
trend of their potential customers which will help to maintain their revenue. Sales predication is very helpful for the people as it difficult to calculate but is this is every business want to keep them in their business. A great deal of new business and private companies can likewise accept the advantage of it as should be obvious the information for the existing organisations and take help with the goal that they can stock the items which will assist them with gaining benefits which can assist them with expanding. On the greater scale the economy can be influenced in a positive path as the business will acquire benefits work will increment. Along these lines, this product will be expected to the organisations and it tends to be great income creating alternative for the product dealers as he/she can offer it to the organisations or can execute the program for them.
How does it work?
First, the metrics are been set for the problem like the monthly revenue, active costumers, prices etc metrics will help use to code on python so that it’s easy to put the data accordingly. Then the data will be loaded in python with the appropriate libraries in the code. Next step, will be to do analysis of the data to show the size of the data how much is the data, what are required things in the data set for the prediction. The data will need to be preprocessed in order to make the compatible to be used. As the data will have of lot of faults in it like missing value, inappropriate values that can be fixed in preprocessing process. The data will the be prepared in order to find the appropriate model which will be used in prediction like linear model and then the data will be tests and the results will be shown.
Proposed Idea
The idea to make a Sales predict web application, which is quite similar to the other application the following tech stack has been used:-
- Python- Keras, TensorFlow in Jupyter Notebook
- For WebApplication — Angular Frontend
- Different Model like linear regression, KNN for prediction there are many libraries for these models.
Jupyter Notebook is an application in which contains the code and other rich element like paragraph equations etc. Keras provides neural network libraries which help to in the making of the equations and it provides High level API’s. TensorFlow is an open source library and TensorFlow provides both High level and small level API’s. These both help to train the data with ease and the effort of the maker reduces because their are pre-made functions stored in libraries which are used by the user.
To predict a certain set of data different models are been used as to find which shows the most accurate result. Linear regression is form of supervised learning which is used in machine learning. Based on independent variables the regression model targets the prediction value. Other model which can be used is K-Nearest Neighbours (KNN) model it is also a form of regression but takes a different approach in KNN calculations use information and arrange new information focuses dependent on similitude measures (for example separation work). Grouping is finished by a greater part vote to its neighbours. The information is allocated to the class which has the closest neighbours. As you increment the quantity of closest neighbours, the estimation of k, precision may increment.

Conclusion
Machine learning is a very vast topic and it is increasing day by day for example in AI cars, fraud detection, healthcare sector. New researches are been made in order to reduce the efforts of humans. Sales prediction can be one of the most important thing done through machine learning as it’s useful for the people who uses it and it can help them increase profits and on greater scale it can help the economy like increase in employment, technology.
