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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Implementing the revised approach


In this section, we will discuss the three parts of implementation, which are as follows:

  • Implementation

  • Testing the revised approach

  • Understanding the problem with the revised approach

Implementation

Here, we are implementing the following:

  • Alignment

  • Smoothing

  • Logistic Regression

We have already discussed the approach and key concepts, so now we just focus on the code part here. You can find all the code at this GitHub link: https://github.com/jalajthanaki/stock_price_prediction/blob/master/Stock_Price_Prediction.ipynb.

Implementing alignment

The alignment is performed on the testing dataset. You can refer to the following code snippet:

Figure 2.30: Code snippet for alignment on the test dataset

As you can see in the preceding code snippet, we obtain a difference of 10 days adj close price using the average price of the last 5 days and the average price of the predicted upcoming 5 days in order to align the test data. Here, we also convert the date from the string into...

You have been reading a chapter from
Machine Learning Solutions
Published in: Apr 2018
Publisher: Packt
ISBN-13: 9781788390040
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