Linear Regression with Python
416 個評分

10,760 人已註冊
Create a linear model, and implement gradient descent.
Train the linear model to fit given data using gradient descent.
416 個評分
10,760 人已註冊
Create a linear model, and implement gradient descent.
Train the linear model to fit given data using gradient descent.
In this 2-hour long project-based course, you will learn how to implement Linear Regression using Python and Numpy. Linear Regression is an important, fundamental concept if you want break into Machine Learning and Deep Learning. Even though popular machine learning frameworks have implementations of linear regression available, it's still a great idea to learn to implement it on your own to understand the mechanics of optimization algorithm, and the training process. Since this is a practical, project-based course, you will need to have a theoretical understanding of linear regression, and gradient descent. We will focus on the practical aspect of implementing linear regression with gradient descent, but not on the theoretical aspect. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Data Science
Deep Learning
Machine Learning
Python Programming
Linear Regression
在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:
Introduction
Dataset
Initialize Parameters
Forward Pass
Compute Loss
Backward Pass
Update Parameters
Training Loop
Predictions
Additional Example
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由 KM 提供
2020年5月14日overall course was good but i certificate i mention course have completed , it would be good if project like statement have mentioned
由 DA 提供
2020年9月1日It was very interesting. I think it should interest more than if using real world data set.
由 AS 提供
2020年6月4日Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.
由 V 提供
2020年8月3日linear Regression with python is very full for project implementation as well as Research data implementation.
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