BEGINNERS GUIDE TO MACHINE LEARNING

BEGINNERS GUIDE TO MACHINE LEARNING

Are you planning to start your career in the field of AI, but having trouble where to give it a go ??

In this article we will give you a complete guide about the steps that should be followed while starting a career in Artificial Intelligence. If you are beginner in the field of AI then you are in the right place. This article is specially designed for you. To give it a go you need to have concept of python/R. Little or no concept about algebra and other mathematics is ok but you need to focus on mathematics now onwards.

A machine learning project may not be linear, but it has a number of well known steps:

  1. Define Problem.
  2. Prepare Data.
  3. Evaluate Algorithms.
  4. Improve Results.
  5. Present Results.

 

  • Start with the Basic

  First, it is important to understand the complete workflow of Python and build a strong foundation in this. Having a good knowledge of the basic syntax, functions, loops, class, and objects is very necessary to move forward. Unless you know the basic syntax, it’s hard to implement anything. That said, don’t spend too long on this. The goal is to learn the very basics, so you know enough to start working on your own projects in your areas(s) of interest.
  • Setup your Computer and install basic libraries 

  There is a vast array of libraries and modules available in Python. Mastering them based on your domain of expertise is necessary. They all have their use cases and functionalities in different domains. For instance, Machine Learning based libraries in Python include Pandas, Numpy, Scikit-learn, Scipy, Matplotlib, etc., Data Analytics based libraries include Bokeh, Matplotlib, PyPlot, etc. Anaconda is an open source distribution for Python and R for large scale data processing, scientific computing and predictive analytics.
  • Start Doing Projects with Further Learning

 Start working on the projects along. Define a problem, prepare datasets, evaluate using the algorithms, keep tracks of the result and keep trying to find the optimal result. You will make mistakes, get stuck many times, but gradually you will find ways to come out of your problems. On the journey of finding answers to your queries you will learn new things and here the real learning will start.
  • Participate in Hackathon, Coding Exams

Keep increasing the difficulty and scope of your projects. If you’re completely comfortable with what you’re building, it means it’s time to try something harder.

Here are some ideas for when that time comes:

  • Try teaching a novice how to do your current project.
  • Try load testing your website — can you scale it up?
  • Can you make your program run faster?
Participate in coding Competitions, hackathons and other exams which can enrich your talent and helps you to increase your efficiency.

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About Diwas Pandey

Highly motivated, strong drive with excellent interpersonal, communication, and team-building skills. Motivated to learn, grow and excel in Data Science, Artificial Intelligence, SEO & Digital Marketing

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