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Developing Kaggle Notebooks

You're reading from   Developing Kaggle Notebooks Pave your way to becoming a Kaggle Notebooks Grandmaster

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781805128519
Length 370 pages
Edition 1st Edition
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Author (1):
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Gabriel Preda Gabriel Preda
Author Profile Icon Gabriel Preda
Gabriel Preda
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Table of Contents (14) Chapters Close

Preface 1. Introducing Kaggle and Its Basic Functions FREE CHAPTER 2. Getting Ready for Your Kaggle Environment 3. Starting Our Travel – Surviving the Titanic Disaster 4. Take a Break and Have a Beer or Coffee in London 5. Get Back to Work and Optimize Microloans for Developing Countries 6. Can You Predict Bee Subspecies? 7. Text Analysis Is All You Need 8. Analyzing Acoustic Signals to Predict the Next Simulated Earthquake 9. Can You Find Out Which Movie Is a Deepfake? 10. Unleash the Power of Generative AI with Kaggle Models 11. Closing Our Journey: How to Stay Relevant and on Top 12. Other Books You May Enjoy
13. Index

Kaggle Learn

Kaggle Learn is one of the lesser-known gems on Kaggle. It contains compact learning modules, each centered on a certain subject related to data science or machine learning. Each learning module has several lessons, each one with a Tutorial section followed by an Exercise section. The Tutorial and Exercise sections are available in the form of interactive Kaggle Notebooks. To complete a learning module, you need to go through all the lessons. In each lesson, you will need to review the training material and successfully run the Exercise Notebook. Some of the cells in the Exercise Notebook have a verification associated with them. If you need help, there are also special cells in the notebook that reveal hints about how to solve the current exercise. Upon completing the entire learning module, you receive a certificate of completion from Kaggle.

Currently, Kaggle Learn is organized into three main sections:

  • Your Courses, where you have the courses that you have completed and those that are now in progress (active).
  • Open courses that you can explore further. The courses in this main section are from absolute beginner courses (such as Intro to Programming, Python, Pandas, Intro to SQL, and Intro to Machine Learning) to intermediate courses (such as Data Cleaning, Intermediate Machine Learning, Feature Engineering, and Advanced SQL). Also, it contains topic-specific courses like Visualization, Geospatial Analysis, Computer Vision, Time Series, and Intro to Game AI and Reinforcement Learning. Some courses touch on extremely interesting topics such as AI ethics and machine learning interpretability.
  • Guides, which is dedicated to various learning guides for programs, frameworks, or domains of interest. This includes the JAX Guide, TensorFlow Guide, Transfer Learning for Computer Vision Guide, Kaggle Competitions Guide, Natural Language Processing Guide, and R Guide.

Kaggle is also committed to supporting continuous learning and helping anyone benefit from the knowledge accumulated on the Kaggle platform and the Kaggle community. In the last two years, Kaggle has started to reach out and help professionals from underrepresented communities acquire skills and experience in data science and machine learning in the form of the KaggleX BIPOC (Black, Indigenous, and People of Color) Grant program, by pairing Kagglers, as mentors, with professionals from BIPOC communities, as mentees.

In the next section, we will familiarize ourselves with a rapidly evolving capability of the Kaggle platform: Models.

You have been reading a chapter from
Developing Kaggle Notebooks
Published in: Dec 2023
Publisher: Packt
ISBN-13: 9781805128519
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