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Linear regression, Regression analysis, Machine learning, Median, Mean squared error, Decision tree learning

@jeremyphoward shared
On May 23, 2022
Also, be sure to give gradient boosting a try too. It's not covered in the notebook, but @the_antlr_guy & I have a whole book chapter about it! https://t.co/KaLcodT7s8
Open

How to explain gradient boosting

3-part article on how gradient boosting works for squared error, absolute error, and general loss functions. Deeply explained, but as simply and intuitively as possible.

@jeremyphoward shared
On May 23, 2022
Also, be sure to give gradient boosting a try too. It's not covered in the notebook, but @the_antlr_guy & I have a whole book chapter about it! https://t.co/KaLcodT7s8
Open
How to explain gradient boosting

How to explain gradient boosting

3-part article on how gradient boosting works for squared error, absolute error, and general loss functions. Deeply explained, but as simply and intuitively as possible.

An End-to-End Guide to Understand the Math behind XGBoost

An End-to-End Guide to Understand the Math behind XGBoost

Ever since its introduction in 2014, XGBoost has been lauded as the holy grail of machine learning hackathons and competitions. From…

#003 PyTorch – How to implement Linear Regression in PyTorch

#003 PyTorch – How to implement Linear Regression in PyTorch

You will learn what Linear regression is and we will show you an easy way to use PyTorch to implement a simple linear regression model.

15 Popular Machine Learning Metrics For Data Scientist

15 Popular Machine Learning Metrics For Data Scientist

The article was about the popular machine learning metrics. We described fifteen of them here. We hope, this would be very helpful for you.

Beware Default Random Forest Importances

Beware Default Random Forest Importances

Training a model that accurately predicts outcomes is great, but most of the time you don't just need predictions, you want to be able to interpret your model. The problem is that the ...

3 Reasons Data Scientists Need Linear Algebra

3 Reasons Data Scientists Need Linear Algebra

As a data scientist, you may be able to get away without using linear algebra — but not for long. Here’s how linear algebra can improve your machine learning, computer vision and natural ...

Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

Analyzing the roles of NP physicochemical properties, tumor models, and cancer types in NP tumor delivery efficiency

Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate

Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate

The application of recycled aggregate as a sustainable material in construction projects is considered a promising approach to decrease the carbon footprint of concrete structures. ...

Azure Machine Learning- Predicting the Value of Your House

Azure Machine Learning- Predicting the Value of Your House

In this tutorial you will learn how to build a model to predict the real estate sales price of a house based upon various historical features about the house and the sales transaction.

Understanding Gradient Boosting as a gradient descent

Understanding Gradient Boosting as a gradient descent

Understanding Gradient Boosting as a gradient descent

Going beyond least-squares – II : Self-concordant analysis for logistic regression

Going beyond least-squares – II : Self-concordant analysis for logistic regression

Generalization bounds for generalized linear models Beyond optimization, the use of self-concordant can make the non-asymptotic statistical analysis of logistic regression, and more ...

What Is Gradient Boosting?

What Is Gradient Boosting?

A common type of machine learning model that has managed to be extremely useful in data science competitions is a gradient boosting model. Gradient boosting is basically the process of ...