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Patrick Curtis - Applied Machine Learning

Patrick Curtis – Applied Machine Learning

Original price was: $197.00.Current price is: $50.40.

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Purchase Patrick Curtis – Applied Machine Learning Course at GiOlib. We actively participate in group buys and are committed to sharing knowledge with a wider audience. What's more, our courses maintain the same quality as the original sale page. You have the option to buy directly from the sale page at the full price (sale page link is provided within the post).

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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

Purchase the Patrick Curtis – Applied Machine Learning course at the best price at GiOlib. Upon completing your purchase, you will gain access to the downloads page. where you can conveniently retrieve all associated course files. Additionally, we will send you a download notification email to your registered mail.

Unlock your full potential with our Patrick Curtis – Applied Machine Learning courses. Our courses are meticulously designed to empower you with the skills and knowledge needed for excellence.

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