Regression

Top 10 Machine Learning Algorithms Every Programmer Should Know #1. Linear Regression: The Oldie but Goodie #2. Logistic Regression: It’s Not All About Numbers #3. Decision Trees:...

Boosting Your Method to SuccessImagine running a relay race. Each runner improves upon the previous one’s performance, and together, they win the race. That’s how these algorithms work — every latest model compensates for...

Exploring Gradient Boosting vs Linear Regression: Selecting the Best Prediction Tool and Developing a Streamlit App Creating your project’s environment Using VSCode for data evaluation Data Treatment Data...

Hey there! I’m Ana, a knowledge enthusiast and a machine learning apprentice. Welcome to my first post on Medium, where I’ll be sharing my journey and insights into the exciting world of knowledge evaluation...

Deep Dive into Softmax Regression Background: Multi-Class Classification Problems The Softmax Regression Model Cross-Entropy Loss Gradient Descent Practice Query Softmax Regression in Scikit-Learn Summary

With these gradients, we will use (stochastic) gradient descent to reduce the loss function on the given training set.You might be given a set of images and you must classify them into dogs/cats and...

The Matrix Algebra of Linear Regression

Looking under the hood on the matrix operations behind linear regression11 min read·12 hours agoFitted ValuesWe've got now used some linear algebra to seek out the best-fitting parameters for a straightforward linear regression model....

A Comprehensive Overview of Regression Evaluation Metrics

Principally, all metrics exploded in size, which is intuitively consistent. That will not be the case for sMAPE, which stayed the identical between each cases.I highly encourage you to mess around with such toy...

Linear Regression In Depth (Part 2) Multiple Linear Regression Definition Closed-Form Solution Multiple Linear Regression Example Linear Regression in Scikit-Learn Analyzing the Regression Errors Gradient Descent The SGDRegressor Class Key Takeaways

Deep Dive into Multiple Linear Regression with Examples in PythonLet’s reduce the training rate from 0.01 to 0.001 by changing the parameter eta0 of the SGDRegressor:pipeline.set_params(reg__eta0=0.001)Let’s refit the pipeline to the training set and...

Linear Regression to GPT in Seven Steps Step 1: Prediction by Linear Regression Step 2: Prediction by Neural Networks Step 3: Prediction on a word Step 4: Prediction...

How the common-or-garden prediction method shows us the method to Generative AIThere are many writings about Generative AI. There are essays dedicated to its applications, ethical and moral issues, and its risk to human...

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