Merge pull request #881 from microsoft/copilot/fix-71909546-a940-4e0f-a408-e6e2cae01d9f
[Documentation] Create comprehensive troubleshooting guidepull/883/head
commit
7b1e824062
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# Support
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# Support
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## How to file issues and get help
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## How to file issues and get help
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Before filing an issue, please check our [Troubleshooting Guide](TROUBLESHOOTING.md) for solutions to common problems with installation, setup, and running lessons.
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This project uses GitHub Issues to track bugs and feature requests. Please search the existing
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This project uses GitHub Issues to track bugs and feature requests. Please search the existing
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||||||
issues before filing new issues to avoid duplicates. For new issues, file your bug or
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issues before filing new issues to avoid duplicates. For new issues, file your bug or
|
||||||
feature request as a new Issue.
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feature request as a new Issue.
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|
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For help and questions about using this project, file an issue.
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For help and questions about using this project, you can also:
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- Check the [Troubleshooting Guide](TROUBLESHOOTING.md)
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- Visit our [Discord Discussions #ml-for-beginners channel](https://aka.ms/foundry/discord)
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- File an issue
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## Microsoft Support Policy
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## Microsoft Support Policy
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Support for this repository is limited to the resources listed above.
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Support for this repository is limited to the resources listed above.
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@ -0,0 +1,596 @@
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# Troubleshooting Guide
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This guide helps you solve common problems when working with the Machine Learning for Beginners curriculum. If you don't find a solution here, please check our [Discord Discussions](https://aka.ms/foundry/discord) or [open an issue](https://github.com/microsoft/ML-For-Beginners/issues).
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## Table of Contents
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- [Installation Issues](#installation-issues)
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- [Jupyter Notebook Issues](#jupyter-notebook-issues)
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- [Python Package Issues](#python-package-issues)
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- [R Environment Issues](#r-environment-issues)
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- [Quiz Application Issues](#quiz-application-issues)
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- [Data and File Path Issues](#data-and-file-path-issues)
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- [Common Error Messages](#common-error-messages)
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- [Performance Issues](#performance-issues)
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- [Environment and Configuration](#environment-and-configuration)
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---
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## Installation Issues
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### Python Installation
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**Problem**: `python: command not found`
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**Solution**:
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1. Install Python 3.8 or higher from [python.org](https://www.python.org/downloads/)
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2. Verify installation: `python --version` or `python3 --version`
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3. On macOS/Linux, you may need to use `python3` instead of `python`
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**Problem**: Multiple Python versions causing conflicts
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**Solution**:
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```bash
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# Use virtual environments to isolate projects
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python -m venv ml-env
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# Activate virtual environment
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# On Windows:
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ml-env\Scripts\activate
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# On macOS/Linux:
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source ml-env/bin/activate
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```
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### Jupyter Installation
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**Problem**: `jupyter: command not found`
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**Solution**:
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```bash
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# Install Jupyter
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pip install jupyter
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# Or with pip3
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pip3 install jupyter
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# Verify installation
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jupyter --version
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```
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**Problem**: Jupyter won't launch in browser
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**Solution**:
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```bash
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# Try specifying the browser
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jupyter notebook --browser=chrome
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# Or copy the URL with token from terminal and paste in browser manually
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# Look for: http://localhost:8888/?token=...
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```
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### R Installation
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**Problem**: R packages won't install
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**Solution**:
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```r
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# Ensure you have the latest R version
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# Install packages with dependencies
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install.packages(c("tidyverse", "tidymodels", "caret"), dependencies = TRUE)
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# If compilation fails, try installing binary versions
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install.packages("package-name", type = "binary")
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```
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**Problem**: IRkernel not available in Jupyter
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**Solution**:
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```r
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# In R console
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install.packages('IRkernel')
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IRkernel::installspec(user = TRUE)
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```
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---
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## Jupyter Notebook Issues
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### Kernel Issues
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**Problem**: Kernel keeps dying or restarting
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**Solution**:
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1. Restart the kernel: `Kernel → Restart`
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2. Clear output and restart: `Kernel → Restart & Clear Output`
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3. Check for memory issues (see [Performance Issues](#performance-issues))
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4. Try running cells individually to identify problematic code
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**Problem**: Wrong Python kernel selected
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**Solution**:
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1. Check current kernel: `Kernel → Change Kernel`
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2. Select the correct Python version
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3. If kernel is missing, create it:
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```bash
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python -m ipykernel install --user --name=ml-env
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```
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**Problem**: Kernel won't start
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**Solution**:
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```bash
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# Reinstall ipykernel
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pip uninstall ipykernel
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pip install ipykernel
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# Register the kernel again
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python -m ipykernel install --user
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```
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### Notebook Cell Issues
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**Problem**: Cells are running but not showing output
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**Solution**:
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1. Check if cell is still running (look for `[*]` indicator)
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2. Restart kernel and run all cells: `Kernel → Restart & Run All`
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3. Check browser console for JavaScript errors (F12)
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**Problem**: Can't run cells - no response when clicking "Run"
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**Solution**:
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1. Check if Jupyter server is still running in terminal
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2. Refresh the browser page
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3. Close and reopen the notebook
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4. Restart Jupyter server
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---
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## Python Package Issues
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### Import Errors
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**Problem**: `ModuleNotFoundError: No module named 'sklearn'`
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**Solution**:
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```bash
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pip install scikit-learn
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# Common ML packages for this course
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pip install scikit-learn pandas numpy matplotlib seaborn
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```
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**Problem**: `ImportError: cannot import name 'X' from 'sklearn'`
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**Solution**:
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```bash
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# Update scikit-learn to latest version
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pip install --upgrade scikit-learn
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# Check version
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python -c "import sklearn; print(sklearn.__version__)"
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```
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### Version Conflicts
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**Problem**: Package version incompatibility errors
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**Solution**:
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```bash
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# Create a new virtual environment
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python -m venv fresh-env
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source fresh-env/bin/activate # or fresh-env\Scripts\activate on Windows
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# Install packages fresh
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pip install jupyter scikit-learn pandas numpy matplotlib seaborn
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# If specific version needed
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pip install scikit-learn==1.3.0
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```
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**Problem**: `pip install` fails with permission errors
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**Solution**:
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```bash
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# Install for current user only
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pip install --user package-name
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# Or use virtual environment (recommended)
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python -m venv venv
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source venv/bin/activate
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pip install package-name
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```
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### Data Loading Issues
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**Problem**: `FileNotFoundError` when loading CSV files
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**Solution**:
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```python
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import os
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# Check current working directory
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print(os.getcwd())
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# Use relative paths from notebook location
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df = pd.read_csv('../../data/filename.csv')
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# Or use absolute paths
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df = pd.read_csv('/full/path/to/data/filename.csv')
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```
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---
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## R Environment Issues
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### Package Installation
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**Problem**: Package installation fails with compilation errors
|
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**Solution**:
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```r
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# Install binary version (Windows/macOS)
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install.packages("package-name", type = "binary")
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# Update R to latest version if packages require it
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# Check R version
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R.version.string
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# Install system dependencies (Linux)
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# For Ubuntu/Debian, in terminal:
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# sudo apt-get install r-base-dev
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```
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|
**Problem**: `tidyverse` won't install
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**Solution**:
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```r
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# Install dependencies first
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install.packages(c("rlang", "vctrs", "pillar"))
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# Then install tidyverse
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install.packages("tidyverse")
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# Or install components individually
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install.packages(c("dplyr", "ggplot2", "tidyr", "readr"))
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```
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|
### RMarkdown Issues
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|
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|
**Problem**: RMarkdown won't render
|
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|
**Solution**:
|
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|
```r
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# Install/update rmarkdown
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install.packages("rmarkdown")
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# Install pandoc if needed
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install.packages("pandoc")
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# For PDF output, install tinytex
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install.packages("tinytex")
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tinytex::install_tinytex()
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|
```
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|
---
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|
## Quiz Application Issues
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|
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|
### Build and Installation
|
||||||
|
|
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|
**Problem**: `npm install` fails
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||||||
|
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|
**Solution**:
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||||||
|
```bash
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|
# Clear npm cache
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|
npm cache clean --force
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# Remove node_modules and package-lock.json
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rm -rf node_modules package-lock.json
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# Reinstall
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npm install
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# If still fails, try with legacy peer deps
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npm install --legacy-peer-deps
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```
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|
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||||||
|
**Problem**: Port 8080 already in use
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```bash
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|
# Use different port
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npm run serve -- --port 8081
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|
# Or find and kill process using port 8080
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|
# On Linux/macOS:
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|
lsof -ti:8080 | xargs kill -9
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|
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|
# On Windows:
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|
netstat -ano | findstr :8080
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taskkill /PID <PID> /F
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|
```
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|
### Build Errors
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|
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||||||
|
**Problem**: `npm run build` fails
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|
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|
**Solution**:
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|
```bash
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# Check Node.js version (should be 14+)
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node --version
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# Update Node.js if needed
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# Then clean install
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rm -rf node_modules package-lock.json
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npm install
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npm run build
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```
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|
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|
**Problem**: Linting errors preventing build
|
||||||
|
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||||||
|
**Solution**:
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||||||
|
```bash
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|
# Fix auto-fixable issues
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npm run lint -- --fix
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|
|
||||||
|
# Or temporarily disable linting in build
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||||||
|
# (not recommended for production)
|
||||||
|
```
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|
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|
---
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||||||
|
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||||||
|
## Data and File Path Issues
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||||||
|
|
||||||
|
### Path Problems
|
||||||
|
|
||||||
|
**Problem**: Data files not found when running notebooks
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
1. **Always run notebooks from their containing directory**
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||||||
|
```bash
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|
cd /path/to/lesson/folder
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|
jupyter notebook
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||||||
|
```
|
||||||
|
|
||||||
|
2. **Check relative paths in code**
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||||||
|
```python
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|
# Correct path from notebook location
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|
df = pd.read_csv('../data/filename.csv')
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|
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||||||
|
# Not from your terminal location
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||||||
|
```
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||||||
|
|
||||||
|
3. **Use absolute paths if needed**
|
||||||
|
```python
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|
import os
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|
base_path = os.path.dirname(os.path.abspath(__file__))
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||||||
|
data_path = os.path.join(base_path, 'data', 'filename.csv')
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|
```
|
||||||
|
|
||||||
|
### Missing Data Files
|
||||||
|
|
||||||
|
**Problem**: Dataset files are missing
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
1. Check if data should be in the repository - most datasets are included
|
||||||
|
2. Some lessons may require downloading data - check lesson README
|
||||||
|
3. Ensure you've pulled the latest changes:
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||||||
|
```bash
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||||||
|
git pull origin main
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||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Common Error Messages
|
||||||
|
|
||||||
|
### Memory Errors
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||||||
|
|
||||||
|
**Error**: `MemoryError` or kernel dies when processing data
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
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|
# Load data in chunks
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||||||
|
for chunk in pd.read_csv('large_file.csv', chunksize=10000):
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|
process(chunk)
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||||||
|
|
||||||
|
# Or read only needed columns
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||||||
|
df = pd.read_csv('file.csv', usecols=['col1', 'col2'])
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||||||
|
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||||||
|
# Free memory when done
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||||||
|
del large_dataframe
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||||||
|
import gc
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|
gc.collect()
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||||||
|
```
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||||||
|
|
||||||
|
### Convergence Warnings
|
||||||
|
|
||||||
|
**Warning**: `ConvergenceWarning: Maximum number of iterations reached`
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
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||||||
|
from sklearn.linear_model import LogisticRegression
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||||||
|
|
||||||
|
# Increase max iterations
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||||||
|
model = LogisticRegression(max_iter=1000)
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||||||
|
|
||||||
|
# Or scale your features first
|
||||||
|
from sklearn.preprocessing import StandardScaler
|
||||||
|
scaler = StandardScaler()
|
||||||
|
X_scaled = scaler.fit_transform(X)
|
||||||
|
```
|
||||||
|
|
||||||
|
### Plotting Issues
|
||||||
|
|
||||||
|
**Problem**: Plots not showing in Jupyter
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
|
||||||
|
# Enable inline plotting
|
||||||
|
%matplotlib inline
|
||||||
|
|
||||||
|
# Import pyplot
|
||||||
|
import matplotlib.pyplot as plt
|
||||||
|
|
||||||
|
# Show plot explicitly
|
||||||
|
plt.plot(data)
|
||||||
|
plt.show()
|
||||||
|
```
|
||||||
|
|
||||||
|
**Problem**: Seaborn plots look different or throw errors
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
|
||||||
|
import warnings
|
||||||
|
warnings.filterwarnings('ignore', category=UserWarning)
|
||||||
|
|
||||||
|
# Update to compatible version
|
||||||
|
# pip install --upgrade seaborn matplotlib
|
||||||
|
```
|
||||||
|
|
||||||
|
### Unicode/Encoding Errors
|
||||||
|
|
||||||
|
**Problem**: `UnicodeDecodeError` when reading files
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
|
||||||
|
# Specify encoding explicitly
|
||||||
|
df = pd.read_csv('file.csv', encoding='utf-8')
|
||||||
|
|
||||||
|
# Or try different encoding
|
||||||
|
df = pd.read_csv('file.csv', encoding='latin-1')
|
||||||
|
|
||||||
|
# For errors='ignore' to skip problematic characters
|
||||||
|
df = pd.read_csv('file.csv', encoding='utf-8', errors='ignore')
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Performance Issues
|
||||||
|
|
||||||
|
### Slow Notebook Execution
|
||||||
|
|
||||||
|
**Problem**: Notebooks are very slow to run
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
1. **Restart kernel to free memory**: `Kernel → Restart`
|
||||||
|
2. **Close unused notebooks** to free resources
|
||||||
|
3. **Use smaller data samples for testing**:
|
||||||
|
```python
|
||||||
|
# Work with subset during development
|
||||||
|
df_sample = df.sample(n=1000)
|
||||||
|
```
|
||||||
|
4. **Profile your code** to find bottlenecks:
|
||||||
|
```python
|
||||||
|
%time operation() # Time single operation
|
||||||
|
%timeit operation() # Time with multiple runs
|
||||||
|
```
|
||||||
|
|
||||||
|
### High Memory Usage
|
||||||
|
|
||||||
|
**Problem**: System running out of memory
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```python
|
||||||
|
# Check memory usage
|
||||||
|
df.info(memory_usage='deep')
|
||||||
|
|
||||||
|
# Optimize data types
|
||||||
|
df['column'] = df['column'].astype('int32') # Instead of int64
|
||||||
|
|
||||||
|
# Drop unnecessary columns
|
||||||
|
df = df[['col1', 'col2']] # Keep only needed columns
|
||||||
|
|
||||||
|
# Process in batches
|
||||||
|
for batch in np.array_split(df, 10):
|
||||||
|
process(batch)
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Environment and Configuration
|
||||||
|
|
||||||
|
### Virtual Environment Issues
|
||||||
|
|
||||||
|
**Problem**: Virtual environment not activating
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```bash
|
||||||
|
# Windows
|
||||||
|
python -m venv venv
|
||||||
|
venv\Scripts\activate.bat
|
||||||
|
|
||||||
|
# macOS/Linux
|
||||||
|
python3 -m venv venv
|
||||||
|
source venv/bin/activate
|
||||||
|
|
||||||
|
# Check if activated (should show venv name in prompt)
|
||||||
|
which python # Should point to venv python
|
||||||
|
```
|
||||||
|
|
||||||
|
**Problem**: Packages installed but not found in notebook
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```bash
|
||||||
|
# Ensure notebook uses the correct kernel
|
||||||
|
# Install ipykernel in your venv
|
||||||
|
pip install ipykernel
|
||||||
|
python -m ipykernel install --user --name=ml-env --display-name="Python (ml-env)"
|
||||||
|
|
||||||
|
# In Jupyter: Kernel → Change Kernel → Python (ml-env)
|
||||||
|
```
|
||||||
|
|
||||||
|
### Git Issues
|
||||||
|
|
||||||
|
**Problem**: Can't pull latest changes - merge conflicts
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
```bash
|
||||||
|
# Stash your changes
|
||||||
|
git stash
|
||||||
|
|
||||||
|
# Pull latest
|
||||||
|
git pull origin main
|
||||||
|
|
||||||
|
# Reapply your changes
|
||||||
|
git stash pop
|
||||||
|
|
||||||
|
# If conflicts, resolve manually or:
|
||||||
|
git checkout --theirs path/to/file # Take remote version
|
||||||
|
git checkout --ours path/to/file # Keep your version
|
||||||
|
```
|
||||||
|
|
||||||
|
### VS Code Integration
|
||||||
|
|
||||||
|
**Problem**: Jupyter notebooks won't open in VS Code
|
||||||
|
|
||||||
|
**Solution**:
|
||||||
|
1. Install Python extension in VS Code
|
||||||
|
2. Install Jupyter extension in VS Code
|
||||||
|
3. Select correct Python interpreter: `Ctrl+Shift+P` → "Python: Select Interpreter"
|
||||||
|
4. Restart VS Code
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Additional Resources
|
||||||
|
|
||||||
|
- **Discord Discussions**: [Ask questions and share solutions in the #ml-for-beginners channel](https://aka.ms/foundry/discord)
|
||||||
|
- **Microsoft Learn**: [ML for Beginners modules](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum)
|
||||||
|
- **Video Tutorials**: [YouTube Playlist](https://aka.ms/ml-beginners-videos)
|
||||||
|
- **Issue Tracker**: [Report bugs](https://github.com/microsoft/ML-For-Beginners/issues)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Still Having Issues?
|
||||||
|
|
||||||
|
If you've tried the solutions above and still experiencing problems:
|
||||||
|
|
||||||
|
1. **Search existing issues**: [GitHub Issues](https://github.com/microsoft/ML-For-Beginners/issues)
|
||||||
|
2. **Check discussions in Discord**: [Discord Discussions](https://aka.ms/foundry/discord)
|
||||||
|
3. **Open a new issue**: Include:
|
||||||
|
- Your operating system and version
|
||||||
|
- Python/R version
|
||||||
|
- Error message (full traceback)
|
||||||
|
- Steps to reproduce the problem
|
||||||
|
- What you've already tried
|
||||||
|
|
||||||
|
We're here to help! 🚀
|
Loading…
Reference in new issue