AI/ML Techniques

From Data to Insights: A Beginner’s Journey in Exploratory Data Analysis

Every industry uses data to make smarter decisions. But raw data can be messy and hard to understand. EDA allows…

2 months ago

5 Real-World Machine Learning Projects You Can Build This Weekend

Building machine learning projects using real-world datasets is an effective way to apply what you’ve learned. Working with real-world datasets…

2 months ago

Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination

Sample language model responses to different varieties of English and native speaker reactions. ChatGPT does amazingly well at communicating with…

2 months ago

The Concise Guide to Feature Engineering for Better Model Performance

Feature engineering helps make models work better. It involves selecting and modifying data to improve predictions. This article explains feature…

2 months ago

Automating Data Cleaning Processes with Pandas

Few data science projects are exempt from the necessity of cleaning data. Data cleaning encompasses the initial steps of preparing…

2 months ago

Filling the Gaps: A Comparative Guide to Imputation Techniques in Machine Learning

In our previous exploration of penalized regression models such as Lasso, Ridge, and ElasticNet, we demonstrated how effectively these models…

2 months ago

Comparing Scikit-Learn and TensorFlow for Machine Learning

Choosing a machine learning (ML) library to learn and utilize is essential during the journey of mastering this enthralling discipline…

2 months ago

Scaling to Success: Implementing and Optimizing Penalized Models

This post will demonstrate the usage of Lasso, Ridge, and ElasticNet models using the Ames housing dataset. These models are…

2 months ago

Tips for Using Machine Learning in Fraud Detection

The battle against fraud has become more intense than it ever has been. As transactions become increasingly digital and complex,…

2 months ago

Detecting and Overcoming Perfect Multicollinearity in Large Datasets

One of the significant challenges statisticians and data scientists face is multicollinearity, particularly its most severe form, perfect multicollinearity. This…

2 months ago