Stop Thinking. Start Learning.

Follow this to rock DS World!

Machine Learning is like teenage sex; everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.

Before I start with the path in detail, make it clear to yourself that this will demand effort and time from your end.

Choose a Language

If both the languages given are new to you, I’d suggest you to start with Python. If you already know R, first follow this path in R. You can shift to Python later.

  1. Python: If you have no background in programming, start learning from https://learnpythonthehardway.org/. For someone who knows Java or C++ and wants to start Python, first complete this course by Codecademy. Next, you can go to depths with New Boston tutorials.
  2. R: One of the best courses for starting Data Science with R is AnalyticsEdge on edX. It helps you in learning R package, and the implementation of basic algorithms as well.

Study Machine Learning

This is the most important and tough phase in becoming a Data Scientist. 90% people give up midway. Just stay determined and if you complete this, there’s no stopping you!

  1. Introduction to Statistical Learning by Gareth James: Bible of Statistics in Machine Learning. R users are strongly advised to complete this book religiously. It will teach you in-depths of ML Algorithms and their applications.
  2. Python Machine Learning by Sebastian Raschka: As the name suggests, Python people are expected to go through this to learn how to apply ML practically.

Practical Applications

“Without vision you don’t see, and without practicality the bills don’t get paid.”

  1. Titanic: Machine Learning from Disaster
  2. Forest Cover Type Prediction
  3. Bike Sharing Demand
  4. Telstra Network Disruptions
  5. Taxi Trajectory Prediction

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Akhil Gupta

Graduate Student at the University of Illinois. ML @ deepair. Working towards social good using AI.