Answers for 7 Most Frequently Asked Questions in Machine Learning

This article focuses to answer the common questions that an IT professional or new science graduate may have regarding machine learning.

Albert Christopher
Mar 17 · 5 min read

Machine learning is gaining traction everywhere. Almost all industries are implementing machine learning in their business processes to improve — productivity, marketing, sales, customer satisfaction, and business profit. This has created an interest in many IT professionals and they tend to change their career track. New graduates look forward to having a career in machine learning. Both these groups of people have many questions to ask about machine learning.

Keeping those budding professionals in mind, I have compiled the common questions that might haunt them and answered them here for reference. These answers may serve as a good starter for these aspiring professionals.

1) How do I learn machine learning on my own?

Mastering machine learning enables you to become a Data Scientist, AI/Machine Learning Engineer. It also helps to use ML algorithms for development or add skills to your business analysis toolbox.

As a self-starter, you can follow these steps to excel.

  • Develop a strong foundation in Statistics, programming language like R, and a little Mathematics.

2) What skills are needed for machine learning jobs?

As a job seeker, you should be a potential prospect for the employer. You must have a deeper understanding of Algorithms, Applied Mathematics, Statistics, Probability, Programming languages, Analytical and problem-solving skills.

Here is a list of key skill-sets you must have.

👉Fundamentals:

You must have a clear understanding of fundamentals like -

  • Data structures

👉Programming languages

Though you can start with one language, at one stage in your career, you should know all the languages. It is recommended to learn -

  • R
source: knowledgehut

👉Probability and Statistics

Many ML algorithms are extensions of Statistics. Knowledge in probability and statistics makes your ML projects easy. You should know

  • Probability and its techniques

👉Data modeling and evaluation

To apply standard algorithms, you should learn to choose an -

  • Appropriate accuracy/error measure

👉Applying machine learning algorithms and libraries

Applying machine learning algorithms is essential. For that, you should have a strong understanding of –

  • Gradient descent

👉Software engineering and system design

At the end of the day, your deliverable is software. So, you must understand –

  • How different components fit together

3) What are some algorithms that every machine learning engineer should know?

Learning algorithms helps you solve real-world problems without or with minimal human intervention. Some of the popular algorithms you must know include –

  • Apriori Algorithm

4) How should you start a career in machine learning?

Jumpstart your career in machine learning by following these set rules.

  • Gain a strong basic in Algebra, Calculus, and Statistics

5) Which are the best online courses/certifications for AI/machine learning?

The top three best online certifications are presented here.

  • 1) Artificial Intelligence Engineer (AIE) — Artificial Intelligence Board of America (ARTiBA): In this certification program, you will learn the concepts of ML, supervised and unsupervised learning, Natural Language Processing, Cognitive computing, Reinforced Learning, and Deep Learning. With its global reach, it is the industry standard in professional credibility. You can create your career niche in AI functions across industries and countries.

6) What are some common machine learning interview questions?

It is necessary to understand the AI and ML concepts to clear your interview successfully. Some of the common interview questions are listed below.

  • What is the difference between machine learning and data mining?

7) What are the AI and ML starting salaries (WORLDWIDE)?

According to PayScale, an entry-level ML engineer with less than one-year experience earns an average total compensation of $93,678. A machine learning specialist may earn up to 1 million.

source: payscale

The top respondents are from the companies like Accenture, Apple Inc., Amazon Inc., Microsoft Corp, J.P. Morgan Chase & Co., and Robinson Worldwide Inc.

According to Indeed.com, the average salary for an artificial intelligence engineer in the San Francisco area is approximately $134,135 per year.

Albert Christopher

Written by

Researcher, Writer, AI geek. Love to play with tech. #cobots #coding #algorithms

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