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The-Kaggle-Book-2nd-Edition

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Code Repository for The Kaggle Book 2nd Edition, Published by Packt

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<h1 align="center">
The Kaggle Book, Second Edition</h1>
This is the code repository for <a href ="https://www.packtpub.com/en-us/product/the-kaggle-book-9781835083208"> The Kaggle Book, Second Edition</a>, published by Packt.

<h2 align="center">
Master data science competitions with Machine Learning, GenAI, and LLMs
</h2>

Luca Massaron, Bojan Tunguz, Konrad Banachewicz

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<details open> 
 <summary><h2>About the book</summary>
<a href="https://www.packtpub.com/en-us/product/the-kaggle-book-9781835083208">
<img src="https://content.packt.com/B21215/cover_image_small.jpg" alt="The Kaggle Book, Second Edition height="256px" align="right">
</a>

Kaggle has become the proving ground for millions of data enthusiasts worldwide, offering what no classroom tutorial can match: battle-tested skills built through real-world challenges and the hands-on experience that employers seek. Every competition sharpens your data analysis skills, expands your network within the data scientist community, and gives compelling proof of expertise to unlock career opportunities.
The first book of its kind, The Kaggle Book brings together everything you need to excel in competitions, data science projects, and beyond. This new edition includes fresh content and new chapters on Kaggle Models, time series, and Generative AI competitions, with three Kaggle Grandmasters guiding you through modeling strategies and sharing hard-earned insights accumulated over years of competition.
The book extends far past competition tactics, revealing techniques for tackling image, tabular, and textual data as well as reinforcement learning tasks. You’ll also discover tips for designing better validation schemes and working confidently with both standard and unconventional evaluation metrics.
Whether you want to climb the Kaggle leaderboard, accelerate your data science career, or improve the accuracy of your models, this book is for you.
Join our Discord community of over 1,000 members to learn, share, and grow together!
</details>
<details open> 
 <summary><h2>Key Learnings</summary>
<ul>

<li>Get acquainted with Kaggle as a competition platform</li>

<li>Make the most of Kaggle Notebooks, Datasets, Models and Discussion forums</li>

<li>Build a compelling portfolio of projects and ideas to advance your career</li>

<li>Understand binary and multi-class classification, as well as object detection</li>

<li>Approach NLP and time series problems with greater efficiency</li>

<li>Design k-fold and probabilistic validation schemes and experiment with multiple approaches</li>

<li>Get to grips with common and never-before-seen evaluation metrics</li>

<li>Handle simulation, optimization, and the new Generative AI competitions on Kaggle</li>

</ul>

</details>
<details open>
 <summary><h2>Key Updates & Highlights</h2></summary>
 The structure of the book is reorganized with the addition of two entirely new chapters: Kaggle Models and Generative AI in Kaggle Competitions.
Many original chapters are renumbered to accommodate this new material and are significantly expanded with updated examples and more advanced techniques.

<table>
 <thead>
 <tr>
 <th>Topic</th>
 <th>Why It Matters</th>
 <th>Second Edition Upgrade</th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>Generative AI & LLMs (New Chapter)</td>
 <td>Generative AI is transforming data science—buyers want the latest.</td>
 <td>A full chapter on fine-tuning open-source LLMs, prompt recovery, and building AI assistants using RAG pipelines.</td>
 </tr>
 <tr>
 <td>Validation Techniques</td>
 <td>Accurate validation is the #1 skill in competitive ML—users want practical, advanced tactics.</td>
 <td>Adds time-series-safe cross-validation, including Combinatorial Purged Group K-Fold—critical for finance and temporal data.</td>
 </tr>
 <tr>
 <td>Hyperparameter Optimization</td>
 <td>Users want to improve models fast—especially with modern tools.</td>
 <td>Introduces W&B for experiment tracking and explains subtle GBM differences (XGBoost vs. LightGBM) that affect model performance.</td>
 </tr>
 <tr>
 <td>Modeling for Tabular Data</td>
 <td>Tabular is still the most common Kaggle data type—buyers care deeply about performance.</td>
 <td>Updates include AutoML, deep tabular models like TabPFN, and tools for reproducibility like DVC and MLflow.</td>
 </tr>
 <tr>
 <td>Modeling for LLM/NLP</td>
 <td>NLP continues to grow and evolve—especially with embeddings.</td>
 <td>Highlights embedding LLMs from OpenAI and NVIDIA into classic models, plus advanced text normalization use cases.</td>
 </tr>
 </tbody>
</table>

</details>
<details open> 
 <summary><h2>Chapters</summary>

| Chapters | Colab | Kaggle | Gradient | Studio Lab |
| :-------- | :-------- | :------- | :-------- | :-------- |
| **Chapter 1: Introducing Data Science Competition** | | | | |
| **Chapter 2: Organizing Data with Datasets** | | | | |
| **Chapter 3: Working and Learning with Kaggle Notebooks** | | | | |
| **Chapter 4: Kaggle Models** | | | | |
| **Chapter 5: Leveraging Discussion Forums** | | | | |
| **Chapter 6: Detailing Competition Tasks and Metrics** | | | | |
| <ul><li>ch_06_meta_kaggle.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_06/ch_06_meta_kaggle.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_06/ch_06_meta_kaggle.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_06/ch_06_meta_kaggle.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_06/ch_06_meta_kaggle.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 7: Designing Good Validation Schemes** | | | | |
| <ul><li>ch_07_adversarial-validation-example.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_07/ch_07_adversarial-validation-example.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_07/ch_07_adversarial-validation-example.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_07/ch_07_adversarial-validation-example.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_07/ch_07_adversarial-validation-example.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 8: Modeling for Tabular Competitions** | | | | |
| <ul><li>ch_08_interesting-eda-tsne-umap.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_interesting-eda-tsne-umap.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_interesting-eda-tsne-umap.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_interesting-eda-tsne-umap.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_interesting-eda-tsne-umap.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_08_meta-features-and-target-encoding.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_meta-features-and-target-encoding.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_meta-features-and-target-encoding.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_meta-features-and-target-encoding.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_meta-features-and-target-encoding.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_08_really-not-missing-at-random.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_really-not-missing-at-random.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_really-not-missing-at-random.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_really-not-missing-at-random.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_really-not-missing-at-random.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_08_tutorial-feature-selection-with-boruta-shap.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_tutorial-feature-selection-with-boruta-shap.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_tutorial-feature-selection-with-boruta-shap.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_tutorial-feature-selection-with-boruta-shap.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_08/ch_08_tutorial-feature-selection-with-boruta-shap.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 9: Hyperparameter Optimization** | | | | |
| <ul><li>ch_09_basic-optimization-practices.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_basic-optimization-practices.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_basic-optimization-practices.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_basic-optimization-practices.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_basic-optimization-practices.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_hacking-bayesian-optimization-for-dnns.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization-for-dnns.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization-for-dnns.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization-for-dnns.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization-for-dnns.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_hacking-bayesian-optimization.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_hacking-bayesian-optimization.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_kerastuner-for-imdb.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_kerastuner-for-imdb.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_kerastuner-for-imdb.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_kerastuner-for-imdb.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_kerastuner-for-imdb.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_optuna-bayesian-optimization.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_optuna-bayesian-optimization.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_optuna-bayesian-optimization.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_optuna-bayesian-optimization.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_optuna-bayesian-optimization.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_scikit-optimize-for-lightgbm.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_scikit-optimize-for-lightgbm.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_scikit-optimize-for-lightgbm.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_scikit-optimize-for-lightgbm.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_scikit-optimize-for-lightgbm.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_tracking-experiments-with-wb.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tracking-experiments-with-wb.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tracking-experiments-with-wb.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tracking-experiments-with-wb.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tracking-experiments-with-wb.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_09_tutorial-bayesian-optimization-with-lightgbm.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tutorial-bayesian-optimization-with-lightgbm.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tutorial-bayesian-optimization-with-lightgbm.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tutorial-bayesian-optimization-with-lightgbm.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_09/ch_09_tutorial-bayesian-optimization-with-lightgbm.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 10: Ensembling and Stacking Solutions** | | | | |
| <ul><li>ch_10_ensembling.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_10/ch_10_ensembling.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_10/ch_10_ensembling.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_10/ch_10_ensembling.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_10/ch_10_ensembling.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 11: Modeling for Image Classification and Segmentation** | | | | |
| <ul><li>ch_11_augmentations-examples.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_augmentations-examples.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_augmentations-examples.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_augmentations-examples.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_augmentations-examples.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_data-exploration-overview.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_data-exploration-overview.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_data-exploration-overview.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_data-exploration-overview.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_data-exploration-overview.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_images-classification.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_images-classification.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_images-classification.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_images-classification.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_images-classification.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_object-detection-yolov5.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_object-detection-yolov5.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_object-detection-yolov5.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_object-detection-yolov5.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_object-detection-yolov5.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_prepare-annotations.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_prepare-annotations.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_prepare-annotations.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_prepare-annotations.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_prepare-annotations.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_segmentation-inference.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation-inference.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation-inference.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation-inference.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation-inference.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_11_segmentation.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_11/ch_11_segmentation.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 12: Modeling for Natural Language Processing** | | | | |
| <ul><li>ch_12_nlp-augmentation1.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentation1.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentation1.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentation1.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentation1.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_12_nlp-augmentations4.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentations4.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentations4.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentations4.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_nlp-augmentations4.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_12_qanswering.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_qanswering.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_qanswering.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_qanswering.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_qanswering.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_12_sentiment-extraction.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_sentiment-extraction.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_sentiment-extraction.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_sentiment-extraction.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_sentiment-extraction.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_12_toxic-comments-classification.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_toxic-comments-classification.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_toxic-comments-classification.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_toxic-comments-classification.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_12/ch_12_toxic-comments-classification.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 13: Participating in Generative AI Competitions** | | | | |
| **Chapter 14: Handling Simulation and Optimization Competitions** | | | | |
| <ul><li>ch_14_connectx.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_connectx.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_connectx.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_connectx.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_connectx.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_14_mab-santa.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_mab-santa.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_mab-santa.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_mab-santa.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_mab-santa.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| <ul><li>ch_14_rps-notebook1.ipynb</li></ul> | <a href="https://colab.research.google.com/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_rps-notebook1.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> | <a href="https://www.kaggle.com/kernels/welcome?src=https://github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_rps-notebook1.ipynb"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a> | <a href="https://gradient.run/notebook/github.com/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_rps-notebook1.ipynb"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Open In Gradient"></a> | <a href="https://studiolab.sagemaker.aws/import/github/PacktPublishing/The-Kaggle-Book-2nd-Edition/blob/main/Chapter_14/ch_14_rps-notebook1.ipynb"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open In Studio Lab"></a> |
| **Chapter 15: Creating Your Portfolio of Projects and Ideas** | | | | |
| **Chapter 16: Finding New Professional Opportunities** | | | | |

</details>

<details open> 
 <summary><h2>Requirements for this book</summary>
The Python code in this book has been designed to be run on a Kaggle notebook, without any installation on a local computer. Therefore, don’t worry about what machine you have available or what version of Python packages you should install.

 All you need is a computer with access to the internet and a free Kaggle account. In fact, to run the code on a Kaggle notebook (you will find instructions about the procedure in Chapter 3), you first need to open an account on Kaggle. If you don’t have one yet, just go to www.kaggle.com and follow the instructions on the website.
 

We link to many resources throughout the book that we think you will find helpful. When you encounter a link, we recommend that you explore it: you will find code available on public Kaggle notebooks that you can reuse or further materials to illustrate concepts and ideas that we have discussed in the book.
 </details>

<details> 
 <summary><h2>Get to know Authors</h2></summary>

_Luca Massaron_ is a data scientist with over a decade of experience in transforming data into high impact, innovative artifacts, solving real world problems, and generating value for businesses and stakeholders. He is the author of numerous bestselling books on AI, machine learning, and algorithms. Luca is also a 3x Kaggle Grandmaster who reached number 7 in the worldwide user rankings for his performance in data science competitions. Additionally, he is recognized as a Google Developer Expert GDE in AI, Kaggle, and the cloud.

_Bojan Tunguz_ is the founder and CEO of TabulAI, a start-up focused on applying machine learning and AI to structured-data problems. Before founding TabulAI, he worked at three other machine learning start-ups and most recently at NVIDIA. He holds a PhD in theoretical physics from the University of Illinois and has taught as a professor at three liberal arts colleges.

_Konrad Banachewicz_ holds a PhD in statistics from Vrije Universiteit Amsterdam. His academic work focused on extreme dependency modeling in credit risk. In addition to his research activities, he was a tutor and supervised master's students. He transitioned from classical statistics to data mining and machine learning before “data science” became a buzzword.
Over the next decade, he tackled quantitative analysis problems in various financial institutions, becoming an expert in the full life cycle of a data product. His work spanned high-frequency trading to credit risk, predicting potato prices, and analyzing anomalies in the performance of large-scale industrial equipment. He is a believer in knowledge sharing and also competes on Kaggle.

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<details> 
 <summary><h2>Other Related Books</h2></summary>
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<li><a href="https://www.packtpub.com/en-us/product/the-kaggle-workbook-9781804611210">The Kaggle Workbook</a></li>
 <li><a href="https://www.packtpub.com/en-us/product/mathematics-of-machine-learning-9781837027873">Mathematics of Machine Learning</a></li>
 <li><a href="https://www.amazon.com/Deep-Learning-Math-Workbook-mathematical/dp/1806674777/ref=sr_1_1?dib=eyJ2IjoiMSJ9.pzvG4Ao2exWs1oHLmALl0VqgyIkUjuaeSHgLEAnEVnvcqOhDj6NYVLwx7MrBINKdsA6cgRgR6otiihMg186obovmw-eg9EJT7tV-SWYPRReWOh8IaeCNOUUeUjxYxRalctcaLZhXOwTmAOCjJgJICo3zD6dvGSiyb3CMA59cTnUipoPN-8qhyRIYJ_21V96NmVHmj9nrY3rPKDNOfLEYCXuxn3hpFXcacW1eOTLHxMU.KTCHz7nl-ditflMbrAVUQ8z0GCr2RIWPQRm2fZ1SYH4&dib_tag=se&keywords=Deep+Learning+Math+Workbook&qid=1765354631&sr=8-1">Deep Learning Math Workbook</a></li>
 
</ul>

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The-Kaggle-Book-2nd-Edition

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