Quick-Start Guide

Let’s get started!

Who is this guide for?

This guide is basics 101. We will focus on Python and numpy basics. This guide was generated from the Machine Learning MeetUp held on 2nd December 2017.

First steps

To make sure we don’t run into any Python versioning or other installation issues, we will start with Anaconda-Docker image.

  1. Install Docker on your machine from this link.
  2. Install prebuilt docker image for Anaconda/Python from this link.

Now you’re ready to follow the Basics 101 tutorial.

WARNING: In case you have your own installations for Python/Numpy, you may not find help in fixing installations or version related errors. StackOverFlow would be a good resource to get help in such cases.

Download Basics 101 files

Machine Learning Bangalore Chapter has it’s own Github Repository MLBLR. We will be hosting our content, this site, projects and other resources here. This would be used as our project management tool as well.

We are constantly looking for contributors! 
If you are looking to contribute, just post a comment 
and we will involve you ASAP.

Download Link Download the zip folder hosted at: Basics 101

Shamelessly Stanford

We are shamelessly following the basics taught by Andrej Karpathy taught in Stanford in 2016.

Note: If you are aleady well versed in Python then, you can directly follow half of the content hosted at CS231n. We will cover Computer Vision technologies like OpenCV, dLib, etc. Our Meetups would go through this content, so you get to ask, discuss and get your hands directly in real!

Start the Tutorial

There are three parts to the Basics-101 tutorial:

  1. Python-Numpy Basics
  2. Linear Classifier
  3. Classification

We will first cover Python-Numpy Basics.

Click the button below to start the Python-Numpy Basic tutorial.

Note: We are building a process where you will have to solve problems to go to the next step. Chapters/Tutorials would be locked unless you solve few problems. Till then we hope you follow these tutorials religiously! Open iPython on your end, and then follow the link below:

iPython

Here is the video

Read the latest blog to learn more about this video tutorial :

That’s it!

Stay tuned for the a lot of improvement on this site, next tutorials and content!

To-Do list on our end:
- Fix all the url's on this site
- Post the video for the 2nd Dec Meetup
- Update the Github with new orgalizers
- Get the forum up for discussions
- Set up Test-Driven-Tutorials to make sure, you know what!
- Host a Beer-Meetup Soon!

Updated: