Articles About Machine Learning

5 Free Datasets to Kickstart Your Machine Learning Projects Today

5 Free Datasets to Kickstart Your Machine Learning Projects TodayImage by Editor | Midjourney There are many free datasets online that help you practice and learn. These datasets allow you to try different machine learning techniques and improve your skills. You can find these datasets on platforms like Kaggle and UCI Machine Learning Repository. Here are five free datasets that can help you start your machine learning projects. 1. Iris Dataset Description: The Iris Dataset features information about three types […]

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Calculus for Machine Learning (7-day mini-course)

Calculus for Machine Learning Crash Course.Get familiar with the calculus techniques in machine learning in 7 days. Calculus is an important mathematics technique behind many machine learning algorithms. You don’t always need to know it to use the algorithms. When you go deeper, you will see it is ubiquitous in every discussion on the theory behind a machine learning model. As a practitioner, we are most likely not going to encounter very hard calculus problems. If we need to do […]

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CatBoost Essentials: Building Robust Home Price Prediction Systems

Gradient boosting algorithms are powerful tools for prediction tasks, and CatBoost has gained popularity for its efficient handling of categorical data. This is especially valuable for the Ames Housing dataset, which contains numerous categorical features such as neighborhood, house style, and sale condition. CatBoost excels with categorical features through its innovative “ordered target statistics” approach. Unlike traditional methods that require extensive preprocessing (like one-hot encoding), CatBoost can work directly with categorical variables. It calculates statistics on the target variable for […]

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7 Free Machine Learning Tools Every Beginner Should Master in 2024

7 Free Machine Learning Tools Every Beginner Should Master in 2024Image by Author | Created on Canva As a beginner in machine learning, you should not only understand algorithms but also the broader ecosystem of tools that help in building, tracking, and deploying models efficiently. Remember, the machine learning lifecycle includes everything from model development to version control, and deployment. In this guide, we’ll walk through several tools—libraries and frameworks—that every aspiring machine learning practitioner should familiarize themselves with. These […]

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7 LLM Projects to Boost Your Machine Learning Portfolio

7 LLM Projects to Boost Your Machine Learning PortfolioImage by Author | Created on Canva Large language models (LLMs) are super helpful in a variety of tasks. Building LLM-powered applications can seem quite daunting at first. But all you need are: the ability to code, preferably in Python or TypeScript and a few not-so-fun tasks or problems that you’d like to make simpler (I’m sure you have many!). To build LLM applications, you should be able to run and interact […]

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7 Machine Learning Algorithms Every Data Scientist Should Know

7 Machine Learning Algorithms Every Data Scientist Should KnowImage by Author | Created on Canva As a data scientist, you should be proficient in SQL and Python. But it can be quite helpful to add machine learning to your toolbox, too. You may not always use machine learning as a data scientist. But some problems are better solved using machine learning algorithms instead of programming rule-based systems. This guide covers seven simple yet useful machine learning algorithms. We give a […]

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Industries in Focus: Machine Learning for Cybersecurity Threat Detection

Industries in Focus: Machine Learning for Cybersecurity Threat DetectionImage by Editor | Canva(Background designed by Freepik) Cybersecurity threats are becoming increasingly sophisticated and numerous. To address these challenges, the industry has turned to machine learning (ML) as a tool for detecting and responding to cyber threats. This article explores five key ML models that are making an impact in cybersecurity threat detection, examining their applications and effectiveness in protecting digital assets. Applications of Machine Learning in Cybersecurity Before examining specific […]

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Exploring LightGBM: Leaf-Wise Growth with GBDT and GOSS

LightGBM is a highly efficient gradient boosting framework. It has gained traction for its speed and performance, particularly with large and complex datasets. Developed by Microsoft, this powerful algorithm is known for its unique ability to handle large volumes of data with significant ease compared to traditional methods. In this post, we will experiment with LightGBM framework on the Ames Housing dataset. In particular, we will shed some light on its versatile boosting strategies—Gradient Boosting Decision Tree (GBDT) and Gradient-based One-Side […]

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Navigating Missing Data Challenges with XGBoost

XGBoost has gained widespread recognition for its impressive performance in numerous Kaggle competitions, making it a favored choice for tackling complex machine learning challenges. Known for its efficiency in handling large datasets, this powerful algorithm stands out for its practicality and effectiveness. In this post, we will apply XGBoost to the Ames Housing dataset to demonstrate its unique capabilities. Building on our prior discussion of the Gradient Boosting Regressor (GBR), we will explore key features that differentiate XGBoost from GBR, […]

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Boosting Over Bagging: Enhancing Predictive Accuracy with Gradient Boosting Regressors

Ensemble learning techniques primarily fall into two categories: bagging and boosting. Bagging improves stability and accuracy by aggregating independent predictions, whereas boosting sequentially corrects the errors of prior models, improving their performance with each iteration. This post begins our deep dive into boosting, starting with the Gradient Boosting Regressor. Through its application on the Ames Housing Dataset, we will demonstrate how boosting uniquely enhances models, setting the stage for exploring various boosting techniques in upcoming posts. Let’s get started. Boosting […]

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