Interpreting Data with Advanced Statistical Models

Machine Learning is changing the world and at the very core of machine learning are advanced statistical models. With this course, you will know how to create an ML application for problems that appear at your work and understand the basis behind it
Course info
Rating
(16)
Level
Advanced
Updated
Sep 10, 2019
Duration
3h 9m
Table of contents
Course Overview
Getting Started with Machine Learning
Finding Those Models
Predicting Linear Relationships with Regression
Understanding Regression Models in Depth
The Problem of Correct Classification
Large Margin and Bayesian Classification
The Subtle Art of Not Needing Labels: Unsupervised Learning
Description
Course info
Rating
(16)
Level
Advanced
Updated
Sep 10, 2019
Duration
3h 9m
Description

When you look at the core of machine learning, there are advanced statistical models. In this course, Interpreting Data with Advanced Statistical Models, you will gain the ability to effectively understand how to create an ML application that will be able to revolutionize the problems that appear at your work. First, you will learn the basic of Machine learning. Next, you will discover linear regression in a more general pattern, expanding to multiple and polynomial features. Continuing, you will explore how to classify with Logistic Regression, SVMs, and Bayesian methods. Finally, you will learn the intrinsic patterns of data with unsupervised techniques such as K Means and PCA. When you’re finished with this course, you will have the skills and knowledge of Machine Learning needed to apply it in a real-world application.

About the author
About the author

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi, everyone. My name is Axel Sirota. Welcome to my course, Interpreting Data with Advanced Statistical Models. I am a machine learning engineer at ASAPP, statistician, ML fanatic, and I am very excited to present this to you. Machine learning is changing the world, from an autonomous cars to intelligent homes, and at the very core of machine learning are advanced statistical models. Statistics is what made machine learning what it is and is what will guide us in this triail of predictions. We will build from basic statistics the pillars of supervised and unsupervised learning to help you make a difference. Our journey begins at the basic of machine learning, and it will be a deep dive from the start into how statistics is the power engine of the recommendations we get every day. We will revisit linear regression in a more general pattern, expand to multiple and polynomial features, only to continue learning about classification with logistic regression, SVMs and Bayesian methods. Finally, we will learn the intrinsic patterns of our dataset with unsupervised techniques such as k‑means and PCA. By the end of this course, you will be able to effectively understand how to create an ML application that will be able to revolutionize the problems that appear at your work. You will became the guru of those little tips and tricks that make the difference in the day to day. I hope you will join me on this journey to learn how to interpret data with the Interpreting Data with Advanced Statistical Models course, at Pluralsight.