Saturday 28 December 2019

Stock price prediction is possible.

    Look at my previous article. Since the next goal was clear, I was trying to label my raw data manually one by one in the morning today, and I realized it could be done automatically with python, and I actually did it.  

    What I did

    • Classified price charts into two types, 1. One that the price went up after the period the chart shows. 2. One that the price went down after the period the chart describes. 
    • type 1(sample): promising charts   
  • type 2(sample): unpromising charts 

  • I forced my computer to learn that data with the same method an AI model distinguishes between a dog and a cat.

  • In Training it reached 58% accuracy.

  • In Testing it has 55% accuracy.

What I will do next.

I will make it 75%+

After achieving it, I will upload the code to GitHub.

After the project, I will organize the whole process and explain the techniques. Stay tuned.

I can also increase the number of classes by two by adding drastically up and drastically down. 

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