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From Linear Regression to XGBoost: A Side-by-Side Performance Comparison

Regression is undoubtedly one of the most mainstream tasks machine learning models can address.

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Synthetic Dataset Generation with Faker

In this article, you will learn: • how to use the Faker library in Python to generate various types of synthetic data.

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Building a Plain Seq2Seq Model for Language Translation

This post is divided into five parts; they are: • Preparing the Dataset for Training • Implementing the Seq2Seq Model with LSTM • Training the Seq2Seq Model • Using the Seq2Seq Model • Improving the...

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Zero-Shot and Few-Shot Classification with Scikit-LLM

In this article, you will learn: • how Scikit-LLM integrates large language models like OpenAI's GPT with the Scikit-learn framework for text analysis.

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10 Critical Mistakes that Silently Ruin Machine Learning Projects

Machine learning projects can be as exciting as they are challenging.

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Image Augmentation Techniques to Boost Your CV Model Performance

In this article, you will learn: the purpose and benefits of image augmentation techniques in computer vision for improving model generalization and diversity.

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Beyond Pandas: 7 Advanced Data Manipulation Techniques for Large Datasets

If you've worked with data in Python, chances are you've used Pandas many times.

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Building a Seq2Seq Model with Attention for Language Translation

This post is divided into four parts; they are: • Why Attnetion Matters: Limitations of Basic Seq2Seq Models • Implementing Seq2Seq Model with Attention • Training and Evaluating the Model • Using the...

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Your First Containerized Machine Learning Deployment with Docker and FastAPI

Deploying machine learning models can seem complex, but modern tools can streamline the process.

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Implementing Advanced Feature Scaling Techniques in Python Step-by-Step

In this article, you will learn: • Why standard scaling methods are sometimes insufficient and when to use advanced techniques.

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