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Best Machine Learning Book for Beginners

You need a mixof different technologies for Data Science projects. Instead of learning many skills, just learn a few. The four main steps of any project are extracting the data, model development, artificial intelligence, and presentation. Attending interviews with many skills is not so easy. So keep the skills short.
A person with many skills can't perform all the work. You had better learn a few skills like Python, MATLAB, Tableau, and RDBMS. So that you can get a job quickly in the data-science project.
Out of Data Science skills, Machine learning is a new concept. Why because you can learn Python, like any other language. Tableau also the same. Here is the area that needs your 60% effort is Machine learning.  Machine Learning best book to start.

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Machine Learning Tutorial - Part:2

Machine learning is a branch of artificial intelligence. Using computing, you will design systems. These systems to behave with AI features, from your end, you need to train them. This process is called Machine Learning. Read my part-1 if you miss it.
machine learning life cycle

The life cycle of machine learning

  • Acquisition - Collect the data 
  • Prepare - Data Cleaning and Quality 
  • Process- Run Machine Tools 
  • Report- Present the Results

Acquire Data

You can acquire data from many sources; it might be data that are held by your organization or open data from the Internet. There might be one data set, or there could be ten or more.

Cleaning of Data

You must come to accept that data will need to be cleaned and checked for quality before any processing can take place. These processes occur during the prepare phase.

Running Machine Learning Scripts

The processing phase is where the work gets done. The machine learning routines that you have created perform this phase.

Reporting

Finally, the results are presented. Reporting can happen in a variety of ways, such as reinvesting the data back into a data store or reporting the results as a spreadsheet or report.

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