机器学习之旅-------Beginner
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来自前辈的一些建议。
Beginner
Discover the "whys" of machine learning.
Identify you self-limiting beliefs that maybe holding you back.
Investigate the basal definitions and concepts for the field.
1. study a Machine Learning Tool.
2. study a Machine Learning DataSet.
3. study a Machine Learning Algorithm.
4. implement a Machine Learning Algorithm.
Small Projects Methodology
Small in time: A projects should not take any longer than 5-15 hours from inception to presentation of results.
this will allow you to complete a small project in a week of nights and weekend time away from your 9-5 job.
Small in scope: A projects should address the most narrow version of the question you are interested in and still be meaningful.
For example, rather than addressing the problem. "write a program that will tell me if tweet will be retweeted ".
in the general case, address the problem just for a specific twitter account for a given time period.
Small in resources: A project should be able to be completed on your desktop or laptop with a connection to the internet, you should
not need exotic software, Web infrastructure, or third party data or service. collect the data you need to file, load it
into memory and attack your narrow question using open source tools.
Additional Project Tips
Write down what you learn: I recommend that you have a tangible work product for every step you take. this could be a note in a
journal, a tweet, a blog post or an open source project. Each work product acts as an anchor and a milestone.
Do not write code unless that is the purpose of the project: This tip is not obvious but may be the biggest in terms of accelerating your
understanding of machine learning.
The goal is for you to learn something not to create the a unique resource, Do not worry that no one will read studies or tutorials or
notes on an algorithm. They are your perspective and your work product to demonstrate that you now know something.
来源:http://machinelearningmastery.com
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