AI/ML Techniques

10 Must-Know Python Libraries for Machine Learning in 2024

As we progress through 2024, machine learning (ML) continues to evolve at a rapid pace. Python, with its rich ecosystem…

2 months ago

Capturing Curves: Advanced Modeling with Polynomial Regression

When we analyze relationships between variables in machine learning, we often find that a straight line doesn’t tell the whole…

2 months ago

A Gentle Introduction to Bayesian Statistics

Bayesian statistics constitute one of the not-so-conventional subareas within statistics, based on a particular vision of the concept of probabilities.…

3 months ago

Interpreting Coefficients in Linear Regression Models

Linear regression models are foundational in machine learning. Merely fitting a straight line and reading the coefficient tells a lot.…

3 months ago

Basic Statistical Analysis with NumPy

Introduction Statistical analysis is important in data science. It helps us understand data better. NumPy is a key Python library…

3 months ago

3 Ways of Using Gemma 2 Locally

After the highly successful launch of Gemma 1, the Google team introduced an even more advanced model series called Gemma…

3 months ago

7 Machine Learning Projects That Can Add Value to Any Resume

Learning by doing is the best way to master essential skills for becoming a machine learning engineer. Instead of just…

3 months ago

One Hot Encoding: Understanding the “Hot” in Data

Preparing categorical data correctly is a fundamental step in machine learning, particularly when using linear models. One Hot Encoding stands…

3 months ago

The Search for the Sweet Spot in a Linear Regression with Numeric Features

Consistent with the principle of Occam’s razor, starting simple often leads to the most profound insights, especially when piecing together…

3 months ago

Free Tools Every ML Beginner Should Use

We have all experienced it: starting is the toughest part of any journey. So getting started in the ML field…

3 months ago