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Python Unsupervised Learning Guide: Discover the Power of Clustering & PCA | Episode #97
In this episode of PyPod Chronicles, we’re talking about unsupervised learning in a way that’s easy to understand and actually useful.
You’ll learn how techniques like clustering—especially K-Means—a…
Published on 4 months, 2 weeks ago
Feature Engineering 101: Essential Techniques for Model Optimization | Episode #96
In this episode, we get into feature engineering, feature selection, and machine learning techniques that help turn raw data into useful insights.
We’ll cover strategies like correlation analysis, va…
Published on 4 months, 3 weeks ago
ML Model Accuracy Secrets: The Key to Better Predictions & Fewer Errors | Episode #95
Having trouble getting your machine learning models to make accurate predictions?
In this episode of PyPod Chronicles, we break down the biggest mistake most people make—failing to properly evaluate …
Published on 5 months ago
Decision Trees vs. Random Forests vs. XGBoost – Which One Wins in Machine Learning? | Episode #94
In this episode of PyPod Chronicles, we’re breaking down Decision Trees, Random Forests, and XGBoost in a way that actually makes sense.
These machine learning models help solve real-world problems, …
Published on 5 months, 1 week ago
Automate and Optimize Your ML Models: The Power of Pipelines and Feature Engineering | Episode #93
If you’re spending way too much time training machine learning models and not getting the results you want, this episode of PyPod Chronicles is for you.
I’m breaking down a simple but powerful trick …
Published on 5 months, 2 weeks ago
Linear vs. Logistic Regression: When to Use Each in Machine Learning | Episode #92
In this episode of PyPod Chronicles, we're talking about supervised learning and breaking down the difference between linear and logistic regression.
I’ll explain when to use each one and show you ho…
Published on 5 months, 3 weeks ago
Why Good Charts Matter in Machine Learning (And How to Make Them) | Episode #91
In this episode of PyPod Chronicles, I break down how to use Matplotlib and Seaborn to make clear, easy-to-read charts that help prepare data for machine learning.
You'll learn simple tricks to spot …
Published on 6 months ago
Avoid These Mistakes! The Right Way to Encode Categorical Data | Episode #90
Having trouble handling categorical data in machine learning?
In this episode of PyPod Chronicles, we’ll walk you through the best ways to encode it—Label Encoding, One-Hot Encoding, Ordinal Encoding…
Published on 6 months, 1 week ago
Data Preprocessing for Machine Learning: Fix Dirty Data & Boost Accuracy | Episode #89
If you want to build better machine learning models, you need to start with clean, well-prepared data.
In this episode of PyPod Chronicles, we’re breaking down the key steps to getting your data read…
Published on 6 months, 2 weeks ago
Data Quality in AI: The Key to Better Machine Learning Predictions | Episode #88
Want to make your machine learning models work better? It all starts with good, clean data.
In this episode of PyPod Chronicles, we’ll talk about why data quality matters, the biggest mistakes people…
Published on 6 months, 3 weeks ago