Patrick Curtis – Applied Machine Learning

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$197.00 $59.00

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Introducing…

The Wall Street Oasis

APPLIED MACHINE LEARNING

140+ Lessons, 40 Exercises, 3+ hours of video lessons

To Help you Thrive in the Most Prestigious Jobs on Wall Street…

 
HERE’S JUST SOME OF WHAT YOU’LL GET IN THIS COURSE
 
Data Cleaning & Exploration (34 lessons)

This module uses video lessons and 12 exercises to practice exporting and filtering through data using Jupyter Notebook. We will also practice manipulating information by replacing and combining, identifying outliers, and display the data with graphs.

 
Regression Algorithms (4 lessons)

This module uses 4 video lessons to delve deep into regression algorithms, hitting on real relationships, overfitting, and regularization. We will also discuss non-linear relationships and how to model them using decision trees. We then discuss using various ensemble methods.

 
Liquidity Regressor (41 lessons)

This module uses video lessons and 11 exercises to go over how to split data into training and testing sets, construct model pipelines, perform hyperparameter tuning, and cross-validate alternative models to find the top performer. Additionally, we will go over how to evaluate models and visualize predictions.

 
Classification Algorithms (3 lessons)

This module contains 3 video lessons to demonstrate how some learning algorithms are used to solve classification problems. By the end of this module, you will be familiar with Characteristics of Binary Classification Problems, Regularized Logistic Regression Models, and Decision Tree Ensemble Classification Models.

 
Investor Classifier I (30 lessons)

This module uses video lessons and 9 exercises to walk through a business case study. We will perform more advanced data exploration and visualization and engineer features based on conditional relationships between existing features.

 
Investor Classifier II (31 lessons)

This module uses video lessons and 8 exercises to continue the business case study from the previous module. We will go over how to use stratified random sampling, the confusion matrix and its advantages over R^2, and go into detail over AUROC. After this module, you would have built a machine learning classifier from start to finish.

Course Summary – Table Of Contents

Below you will find a list of the modules and lessons included in this course.

 
 
 
 
 
 
Salepage: https://www.wallstreetoasis.com/applied-machine-learning-course-overview
Archive: https://archive.ph/wip/2w1VY

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Patrick Curtis – Applied Machine Learning
Patrick Curtis – Applied Machine Learning

$197.00 $59.00

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