In this chapter, you learned how to predict stock prices. We covered the different machine learning algorithms that can help us in this. We tried Random Forest Regressor, Logistic Regression, and multilayer perceptron. We found out that the multilayer perceptron works really well. I really want to discuss something beyond what we have done so far. If you are under the impression that using the sentiment analysis of news and predictive methods, we can now correctly predict the stock market price with a hundred percent accuracy, then you would be wrong. We can't predict stock prices with a hundred percent accuracy. Many communities, financial organizations, and academic researchers are working in this direction in order to make a stock market price predictive model that is highly accurate. This is an active research area.

So if you are interested in research and freelancing, then you can join some pretty cool communities. There are two communities that are quite popular. One of these is quantopian (https://www.quantopian.com/). In this community, you can submit your stock price prediction algorithm, and if it outperforms other competitors' algorithms, then you will win a cash price, and if you get the license for your algorithm, then you get some profit from transactions that will be done through your licensed algorithm. The second community is numer.ai (https://numer.ai/). This community is similar to quantopian. So, the possibilities of this application are limitless. Both communities offer some great tutorials. So try something different, and hopefully you will come up with a great algorithm.

In the next chapter, we will tap the retail or e-commerce domain and try to figure out some interesting facts about the user behavior dataset and users' social footprint. This will help us understand how the company should change their website or some functionality on the website. What are the chances of the email campaign going well and which type of users will respond to this campaign? Keep reading this book! We will discuss all these things in the next chapter.