Python Machine Learning Bundle

Learn the most fundamental Python functions used in the finance industry, and to build investor classifiers using machine learning algorithms.

Bundle overview

Welcome to CFI's Applied Machine Learning Algorithms Course. The world of finance is changing and now is the time to invest. The skillsets of investment bankers, asset managers, sales and trading professionals are all rapidly evolving. Developing a skillset in machine learning is essential if you want to progress.

Match the Complexity of your Model to the Real Relationship


CFI has partnered with Machine Learning Edge to bring to you the Python Machine Learning bundle. First, in our Python Fundamentals course, you will learn the foundations of Python, used specifically for finance and Excel. Then, in our Applied Machine Learning Algorithms, you’ll utilize the knowledge from Python Fundamentals to build machine learning investor classifiers.

We will explore real case studies from investing banking and capital markets applications being used today to advise Fortune 500 companies all over the world.

Confusion Matrix

By the end of the bundle, you will be able to:

Python Fundamentals

  • Write and execute basic Python code to perform advanced calculation, generate outputs, create variables, abstract from data, etc.
  • Create and manipulate important data structures such as lists, tuples, sets, and dictionaries
  • Use for loops and conditional logic to create your own custom functions
  • Import external packages including NumPy and Pandas
  • Generate random integers and samples
  • Filter, segment, and summarize data
Business Case Overview

Applied Machine Learning Algorithms

  • Identify overfit regression models
  • Compare different regularized regression algorithms and decision tree ensemble algorithms
  • Explain the confusion matrix and its relation to the ROC curve
  • Construct training data sets, testing data sets, and model pipelines
  • Perform advanced data cleaning, exploration, and visualization
  • Engineer features based on conditional relationships between existing features
  • Build and finalize a machine learning classifier
Five Regression Models
Match the Complexity of your Model to the Real Relationship
Confusion Matrix
Business Case Overview
Five Regression Models


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