Getting Started In Machine Learning

Getting Started In Machine Learning

As the new year has unfolded, many of us have set our eyes on the horizon and set goals that we want to achieve in the coming months. If you haven't quiet decided on what skill you would want to acquire as yet, in this article i'll be sharing on how to get started in Machine Learning.

What Is Machine Learning

According to wikipedia Machine Learning (ML) is the study of computer algorithms that improve automatically through experience or in simple terms it's the application of artificial intelligence that provides systems the ability to self-learn and improve any experience required from the given data.

Why Machine Learning

Machine Learning has become a part of our daily lives. From social media,to transport e.g Uber and Bolt (formerly known as Taxify) we use all these products almost everytime and because of this, the machine learning career path has become an in-demand skill.

There are plenty reasons of venturing into machine learning like :

  • Career Advancement

  • Better Salary

  • High Demand In The Job Market

  • Can easily transit into Data Science

How To Get Started

Many people shy away from Machine Learning because they think it's all about Mathematics of which it's not true, although having a basic understanding of linear algebra and probability can be advantageous if you want to know how algorithms work. Now that you have all the basics, let's dive into some of the things that'll help us get started :

  1. Python - most popular Machine Learning libraries are written in python,so learning python is a basic necessity.

  2. Get Acquainted With Python Libraries - getting basic knowledge on python libraries will serve you in the long-run as you'll be constantly using them like :

    • Panda's
    • Numpy
    • Matplotlib
    • Seaborn
    • Scikit-learn
  3. Dive Into Machine Learning Algorithms - learning algorithms and understanding how to apply them to a dataset is a fundamental aspect one has to have like knowing :

    • Linear Regression
    • Decision Trees
    • Logistic Regression
    • KNN
  4. Participate In a Kaggle Competition - entering a kaggle competition will help you put what you are pplearning to the test. Participating in a competition/hackathon has its benefits especially when it comes to skills growth and portfolio building. P

    Conclusion

    In a world where everything is ever evolving, venturing into machine learning will definitely come in handy. Take advantage of such an amazing opportunity and have fun while advancing your skills. Remember

    "The greatest risk is not taking one" Mark Zuckerberg.

Resources

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