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Unsupervised Learning in Trading

1198 Learners
15 hours
Enhance your trading with unsupervised learning algorithms by using concepts like PCA, euclidean distance, WCSS, elbow curve and dimensionality. Create, backtest, paper trade trading strategies using clustering algorithms like k-means and DBSCAN. Perfect for ML Engineers, Python Programmers, Students, Quant Traders, Quant Researchers, and Risk managers.
Level
Intermediate
Author
QuantInsti®
Price Lifetime Access Limited Time Offer

₹10850/-₹43399/-

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  • Live Trading
  • Learning Track
  • Prerequisites
  • Syllabus
  • About author
  • Testimonials
  • Faqs

Live Trading

  • Creating, backtesting and paper trading a trading strategy using a clustering algorithm
  • Creating a list of pairs that are suitable for pairs trading strategy
  • Intuitively and mathematically describe the working of principal component analysis (PCA)
  • Detailed difference between supervised learning algorithms and unsupervised learning algorithms
  • Describe, implement and list the differences between the workings of k-means clustering algorithm and DBSCAN clustering algorithm 
  • Concepts such as euclidean distance, WCSS and interpret elbow curve
  • Curse of dimensionality and various ways to overcome the curse of dimensionality
  • Applications of unsupervised learning
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Skills Covered

learning track 5

This course is a part of the Learning Track: Artificial Intelligence in Trading Advanced

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Full Learning Track

These courses are specially curated to help you with end-to-end learning of the subject.

Need help? Write to us at quantra@quantinsti.com or call us at +91 8450963428.

Course Features

  • Community
    Community

    Faculty Support on Community

  • Interactive Coding Exercises
    Interactive Coding Exercises

    Interactive Coding Practice

  • Capstone Project
    Capstone Project

    Capstone Project Using Real Market Data

  • Trade & Learn Together
    Trade & Learn Together

    Trade and Learn Together

  • Get Certified
    Get Certified

    Get Certified

Prerequisites

A general understanding of trading in the financial markets such as how to place orders to buy and sell is helpful. Basic knowledge of the pandas dataframe and matplotlib would be beneficial to easily work with the codes and trading strategies covered in this course. To learn how to use Python, check out our Free course "Python for Machine Learning in Finance".

Syllabus

about author

QuantInsti®
QuantInsti®
QuantInsti is the world's leading algorithmic and quantitative trading research & training institute with registered users in 190+ countries and territories. An initiative by founders of iRage, one of India’s top HFT firms, QuantInsti has been helping its users grow in this domain through its learning & financial applications based ecosystem for 10+ years.
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Why quantra®?

  • More in Less Time
    More in Less Time

    Gain more in less time

  • Expert Faculty
    Expert Faculty

    Get taught by practitioners

  • Self-paced
    Self-paced

    Learn at your own pace

  • Data & Strategy Models
    Data & Strategy Models

    Get data & strategy models to practice on your own

Faqs

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