└── README.md


/README.md:
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 1 | 
 2 | # Lambda School Machine Learning Mini Bootcamp Day 2
 3 | 
 4 | 1. What is ML
 5 |   * Simple arithmetic applied in great quantities
 6 |   * Programming
 7 |   * Simple (and advanced) calculus
 8 |   * Linear algebra always
 9 | 2. What are the basic tools of ML programming
10 |   * Numerical programming languages:
11 |     * Python
12 |     * R
13 |     * Matlab/Octave
14 |     * Javascript? All the others, too!
15 |   * What are the important requirements of ML languages:
16 |     * Swift data manipulation
17 |     * Robust data APIs
18 |     * Speed
19 |     * Platform independence
20 | 3. Where are ML tools going
21 |   * Design local
22 |   * Share live code and documentation
23 |   * Run remote
24 | 4. Setting up python
25 |   * Local
26 |   * pipenv
27 |   * colaboratory
28 |   * Jupyter
29 |   * Important libs
30 | 
31 | # Assignment
32 | 
33 | Create `yourname_day_2_mlmbc.py`. It must print the result of `54321 * 12345`. Deliver it to me via pull request.
34 | 
35 | 


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