Prerequisite to learn ML?

[Linwood Hayes]

Few questions from newbie thinking about learning ML.

1. Do I need to know Big Data and/or Hadoop to learn ML ?

2. Does ML cover Big data and Hadoop ?

3. Does ML cover SAS and/r R ?

Thank you.

[Campbell Ritchie]

Mostly don';t know. But don't look on a language as a prerequisite for anything. Look on the language as a tool. I know some people metaphorically try using a hammer to drive a screw, but look on different languages as being like driving a nail with a 1lb hammer or a 1½lb hammer or a ½lb hammer.

[Monica Shiralkar]

1. Do I need to know Big Data and/or Hadoop to learn ML ?

A typical scenario is that I would have a big data team where  Java / Scala develpers would processing the  big data and data science team where there would be developers working on Python creating the machine learning models which the big data team would use in their project .

But these days I seeing some requirements where the JD says that the candidates should knowing both big data and ML.

But I think the first case is more common .


2. Does ML cover Big data and Hadoop ?

No .ML comes under AI which in turn comes under data science. Hadoop is ecosystem to processing big data in a cluster .

3. Does ML cover SAS and/r R ?

R is a statistical language and some machine learning models can be in R.

Thank you.

[Zachary Griggs]

My perspective is that the only prerequisite to start learning data science, machine learning & AI is to be familiar with one of the popular programming languages for these applications. For most people, that will be python. A background in math and statistics will help as well; in many ways machine learning is more math than programming. And you can pretty easily pick up python along the way if you know any sort of programming.

Basically what I'm saying is that there's nothing stopping you from getting started with machine learning right now.

Start out with a simple Linear Regression. The linear regression is a way to fit data into a pattern using python, and then you can use that pattern you found in order to predict data you haven't seen before.
Simple tutorial: https://towardsdatascience.com/a-beginners-guide-to-linear-regression-in-python-with-scikit-learn-83a8f7ae2b4f

When you understand that, you can move on to other models, such as a Logistic Regression which is a way to predict either a "yes" or "no" answer based on data: https://towardsdatascience.com/building-a-logistic-regression-in-python-step-by-step-becd4d56c9c8

And just keep researching from there.

[Claude Moore]

Zachary Griggs wrote:A background in math and statistics will help as well; in many ways machine learning is more math than programming. And you can pretty easily pick up python along the way if you know any sort of programming.

Fully agree, except for one thing:a math background is essential, at least if you want to really understand ML. My advice is to read a good book where you can learn theory as well as practical examples .

[Alexey Grigorev]

> 1. Do I need to know Big Data and/or Hadoop to learn ML ?

No, not really. Python (or ability to learn it quickly) and SQL should be enough to get started

> 2. Does ML cover Big data and Hadoop ?

Big data is quite an ambiguous term, it may mean many things. ML doesn't include big data, hadoop or other things. But these tools may be useful for ML, even though Hadoop is not that popular anymore. Often, people use tools like Spark and Flink for doing similar tasks

3. Does ML cover SAS and/r R ?

You can do ML with SAS and R, but Python is de-facto standard these days