#!/usr/bin/env python
# coding: utf-8

# [Table of Contents](00.00-Learning-ML.ipynb#Table-of-Contents) • [← *Chapter 1.01 - Help*](01.01-Help.ipynb) • [*Chapter 2 - Classification* →](02.00-Classification.ipynb)
# 
# ---
# 
# # Chapter 1.02 - Getting Started
# 
# Machine Learning is well supported on all major operating systems, thanks to analytical (...) such Anaconda. Anaconda is an open data science platform that pre-packages many of the required components for data science (and everything for this book!) and can be installed on Windows, OS X and Linux.
# 
# In fact, this entire book is written using components from Anaconda, including Python and R and their machine learning packages, as well as the super helpful Jupyter Notebook which allows for structured and repeatable machine learning.
# 
# ## Installation
# 
# To install Anaconda, follow the instructions for your operating system below:
# 
# * Download and install Anaconda 4.3.0 64-bit from here: [Windows](https://repo.continuum.io/archive/Anaconda3-4.3.0.1-Windows-x86_64.exe), [OS X](https://repo.continuum.io/archive/Anaconda3-4.3.0-MacOSX-x86_64.pkg), [Linux](https://repo.continuum.io/archive/Anaconda3-4.3.0-Linux-x86_64.sh)
# * Update scikit-learn to version 0.18.1: `conda install -c anaconda scikit-learn=0.18.1`
# * Install Keras (and TensorFlow): `pip install keras==2.0.0`
# * Spark and launch Jupyter:
# 
# ```
# sudo gem update --system
# brew install apache-spark
# 
# export SPARK_HOME="/usr/local/Cellar/apache-spark/2.1.0/libexec/"
# export PATH=$PATH:$SPARK_HOME/bin
# export PYSPARK_SUBMIT_ARGS="--master local[2]"
# export PYTHONPATH=$SPARK_HOME/python/:$PYTHONPATH
# export PYTHONPATH=$SPARK_HOME/python/lib/py4j-0.9-src.zip:$PYTHONPATH
# export PYSPARK_DRIVER_PYTHON=jupyter
# export PYSPARK_DRIVER_PYTHON_OPTS='notebook'
# 
# pyspark
# ```
# 
# ## Running Jupyter
# 
# If you've downloaded a copy of this book as Jupyter notebooks, you can run Jupyter `jupyter notebook`. This will open a new browser window with the Jupyter file browser, and you can select the directory containing your notebooks from there.
# 
# ---
# 
# [Table of Contents](00.00-Learning-ML.ipynb#Table-of-Contents) • [← *Chapter 1.01 - Help*](01.01-Help.ipynb) • [*Chapter 2 - Classification* →](02.00-Classification.ipynb)
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