How to Become a Good Machine Learning Engineer

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Are your grades in the A+ line in mathematics? if yes then you will need only one or two steps to take dive into data science. Knowing the problem, and distinct methods to solve it (variations of algorithms), prediction to future which is called analysis.

Do you know how to program some lines of code? A lot of resources are online (Free or Paid ) to learn. If you are good in analytics, and patience to face & resolve issues then it is good for learning machine learning.

Join Facebook groups, social media trends, and google blogs for learning. Then dive into a mini project for learning how the data scientist finds out the patterns of raw facts & figures. Learning through projects will be most helpful for your experience, for example, fake news detection.

Step by Step Guide to Machine Learning

#1 Just Take Initiative

Develop the habit to take the initial steps to understand the working of any model and the origin where it started.

Before diving deep you first should penetrate the stem (basics) of the concepts. There are unlimited open-source codes with implementation, datasets & online free or paid courses to go through the basics. Indeed it is not a good practice but you can add more fruity aspects to advance. For example, you should explore Kaggle where you can win projects and get paid. It’s not too late, take baby steps regularly.

#2 Take Time For Basics

Practice makes a man healthy – an old quote. After learning the basics takes time (3-4 hours) to work on different libraries for manipulating data in its own shape.

In data science, almost every aspect (branch) run with concepts of mathematics, statistics, and analytics. Are you still interested in all those stuff or do even you remember the concept of naive Bayes? You have learned in probability? If you think strongly about finding the answers to a question just like in school then it’s a good point.

Once you got to experience, you are ready to go deeper down the bigger concepts. For example, the working CNN algorithm is used for image classification.

#3 Learn Python Programming Language

Python is a number & c++ is placed in the second position, make sure you are in friendship with it. Initially, you would work with ML models but in long run, you would have to develop your own.

By friendship, I mean, starting to know how OOP concepts, functions, lists, arrays, controls, structures, and loops work. Make sure you know how to print a line on the screen. After all, do not get hesitation into it, spare time for different libraries along with other concepts.

Also Read: Working Of Unsupervised Learnings In Machine Learning

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