Developing Kaggle Notebooks Pave Your Way to Becoming a Kaggle Notebooks Grandmaster
Printed in Color Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact Leverage the power of Generative AI with Kaggle Models Purchase of the print or Kindle book includes a free PDF eBoo...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham, England :
Packt Publishing Ltd
[2023]
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009790332406719 |
Tabla de Contenidos:
- Cover
- Copyright Page
- Forewords
- Contributors
- Table of Contents
- Preface
- Chapter 1: Introducing Kaggle and Its Basic Functions
- The Kaggle platform
- Kaggle Competitions
- Kaggle Datasets
- Kaggle Code
- Kaggle Discussions
- Kaggle Learn
- Kaggle Models
- Summary
- Chapter 2: Getting Ready for Your Kaggle Environment
- What is a Kaggle Notebook?
- How to create notebooks
- Exploring notebook capabilities
- Basic capabilities
- Advanced capabilities
- Setting a notebook as a utility script or adding utility scripts
- Adding and using secrets
- Using Google Cloud services in Kaggle Notebooks
- Upgrading your Kaggle Notebook to Google Cloud AI Notebooks
- Using a Notebook to automatically update a Dataset
- Using the Kaggle API to create, update, download, and monitor your notebooks
- Summary
- Chapter 3: Starting Our Travel - Surviving the Titanic Disaster
- A closer look at the Titanic
- Conducting data inspection
- Understanding the data
- Analyzing the data
- Performing univariate analysis
- Performing multivariate analysis
- Extracting meaningful information from passenger names
- Creating a dashboard showing multiple plots
- Building a baseline model
- Summary
- References
- Chapter 4: Take a Break and Have a Beer or Coffee in London
- Pubs in England
- Data quality check
- Data exploration
- Starbucks around the world
- Preliminary data analysis
- Univariate and bivariate data analysis
- Geospatial analysis
- Pubs and Starbucks in London
- Data preparation
- Geospatial analysis
- Summary
- References
- Chapter 5: Get Back to Work and Optimize Microloans for Developing Countries
- Introducing the Kiva analytics competition
- More data, more insights - analyzing the Kiva data competition
- Understanding the borrower demographic
- Exploring MPI correlation with other factors.
- Radar visualization of poverty dimensions
- Final remarks
- Telling a different story from a different dataset
- The plot
- The actual history
- Conclusion
- Summary
- References
- Chapter 6: Can You Predict Bee Subspecies?
- Data exploration
- Data quality checks
- Exploring image data
- Locations
- Date and time
- Subspecies
- Health
- Others
- Conclusion
- Subspecies classification
- Splitting the data
- Data augmentation
- Building a baseline model
- Iteratively refining the model
- Summary
- References
- Chapter 7: Text Analysis Is All You Need
- What is in the data?
- Target feature
- Sensitive features
- Analyzing the comments text
- Topic modeling
- Named entity recognition
- POS tagging
- Preparing the model
- Building the vocabulary
- Embedding index and embedding matrix
- Checking vocabulary coverage
- Iteratively improving vocabulary coverage
- Transforming to lowercase
- Removing contractions
- Removing punctuation and special characters
- Building a baseline model
- Transformer-based solution
- Summary
- References
- Chapter 8: Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
- Introducing the LANL Earthquake Prediction competition
- Formats for signal data
- Exploring our competition data
- Solution approach
- Feature engineering
- Trend feature and classic STA/LTA
- FFT-derived features
- Features derived from aggregate functions
- Features derived using the Hilbert transform and Hann window
- Features based on moving averages
- Building a baseline model
- Summary
- References
- Chapter 9: Can You Find Out Which Movie Is a Deepfake?
- Introducing the competition
- Introducing competition utility scripts
- Video data utils
- Face and body detection utils
- Metadata exploration
- Video data exploration
- Visualizing sample files.
- Performing object detection
- Summary
- References
- Chapter 10: Unleash the Power of Generative AI with Kaggle Models
- Introducing Kaggle Models
- Prompting a foundation model
- Model evaluation and testing
- Model quantization
- Building a multi-task application with Langchain
- Code generation with Kaggle Models
- Creating a RAG system
- Summary
- References
- Chapter 11: Closing Our Journey: How to Stay Relevant and on Top
- Learn from the best: observe successful Grandmasters
- Revisit and refine your work periodically
- Recognize other's contributions, and add your personal touch
- Be quick: don't wait for perfection
- Be generous: share your knowledge
- Step outside your comfort zone
- Be grateful
- Summary
- References
- Why subscribe?
- PacktPage
- Other Books You May Enjoy
- Index.
