Tuesday, January 26, 2021
Techiexpert.com
No Result
View All Result
  • Login
  • Register
  • Home
  • Tech news
  • Startups
  • AI
  • IOT
  • Big Data
  • Cloud
  • Data Analytics
  • ML
  • Blogging
Techiexpert.com
No Result
View All Result

Guide on How to Become a Machine Learning Engineer

Shreya pandey by Shreya pandey
December 4, 2018
in Machine Learning
Reading Time: 4min read
A A
0
Guide on How to Become a Machine Learning Engineer

https://hackernoon.com/coursera-vs-udacity-for-machine-learning-f9c0d464a0eb

14
SHARES
161
VIEWS
Share on FacebookShare on Twitter

There are numerous creative ways in which machine learning is used behind the scenes to improve everyday lives. IBM’s Chef Watson or ‘smart’ sous chef, for instance, uses machine learning algorithms to help its human counterparts on food combinations to create entirely new flavours. In another example, manufacturers of Barbie have developed a new range of machine learning-powered dolls called “Hello Barbie”. This new range listens and responds to a child from 8,000 statements of dialogue stored on the servers. In the past few years, machine learning has evolved to be much more from just learning algorithms. It has branched out into a variety of niche applications like natural language processing, deep learning, recommendation engines, and reinforcement learning; and the resulting opportunities are nothing short of endless.

Machine learning is now used intrinsically not only in IT, but in consumer goods, retail, energy, creative arts, healthcare, manufacturing, financial services, media, finance, etc., in every imaginable way. So much so, that machine learning now is the reason behind companies churning out exceptional profits. For example, machine learning is such an integral part of Netflix’s video recommendation engine that the company has valued the ROI of these algorithms to stand at £1 billion a year.

Despite numerous innovation in artificial intelligence and machine learning, their involvement in businesses is only expected to grow. According to Monster, the job listings in machine learning have shown a consistent increase, thus making today as perfect a time as any to invest in machine learning courses.

Guide on How to Become a Machine Learning Engineer 1
https://www.forbes.com/sites/louiscolumbus/2018/01/12/10-charts-that-will-change-your-perspective-on-artificial-intelligences-growth/#6ce713a14758

Thus, machine learning is the next big thing in not just IT, but in almost every industrial sector. For those who are interested in pursuing a career in machine learning, here is a step-by-step guide on how to become a machine learning engineer:

ADVERTISEMENT

Basics of R/Python:

While there are a multitude of languages that provide machine learning capabilities, most of the development work is carried out in “R” and “Python”. These are the most commonly used programming languages, and extensive community support is available on both. Before venturing into machine learning, it is essential to focus on either of the two. While both R and Python have their strength and weakness, an efficient machine learning engineer would gain most by diversifying his/her abilities to use whichever applies best in situations of predictive analysis and statistical modelling. That being said, irrespective of which tool you choose to begin with, the focus should always be on understanding the basics, followed by understanding its libraries and data structures.

Learn Descriptive and Inferential Statistics:

Since a variety of machine learning algorithms are based on statistical learning, it is always helpful for machine learning engineers to refresh their knowledge of statistics. To begin with, you can start with understanding the basics of inferential and descriptive statistics. There are many courses available on the web that explain the basics through Excel worksheets and assignments. For those intending to delve deeper into the subject, assignments on descriptive and inferential statistics can be practised using Python and R, and engineers can even refer to the respective methods and statistical libraries. This would help engineers in developing a clear understanding of how machine learning is used in tandem with statistical models.

Data Manipulation:

One of the qualities that differentiate a great machine learning professional from an average one is the ability to manipulate data in any manner possible. This is the skill of discerning which data points would render the required results, and the exploration, cleaning, and preparation of original data. While learning how to manipulate data is a time-consuming process, investing time in this aspect of machine learning would also help you with structuring machine learning algorithms. There is ample literature available on the internet that can be referred to learn more about the different stages of exploration. To go a step further, interested engineers can also refer to various data exploration methods in Python and R.

Enrol in a Machine Learning course:

Now that all the prerequisites are taken care of, the next step is to take up a formal machine learning course. A typical ML course would cover all the underlying algorithms, and would also introduce some popular new-age concepts like recommendation systems, neural networks, deep learning, and the application of machine learning in databases using Map Reduce. Once the basics are done with, the course structure would then cover the advanced machine learning techniques like deep learning, and using the algorithms to harness the benefits of big data.

 Machine Learning libraries:

After building a good grasp on machine learning, the next step is to familiarise yourself with different machine learning frameworks and libraries. These libraries significantly simplify the process of data acquisition, building training models, and generating accurate predictions. Some of the most popular machine learning frameworks are Apache Singa, Amazon Machine Learning, Azure ML Studio, Caffe, H2O, MLib (Spark), Massive Online Analysis (MOA), mlpack, Pattern, Scikit-Learn, Shogun, TensorFlow, Theano, Torch, and Veles.

Roles and expected salary:

Skilled machine engineers can take up a number of job roles, including machine learning engineer, data scientist, data architect, cloud architect, data mining specialists, cybersecurity analysts, and many more. According to the recent industry estimates, the average salary of a machine learning engineer may vary from 8 to 15 lakhs per annum. An experienced professional with two to four years of experience could earn 15-20 lakhs per annum, whereas experienced professionals with 4-8 years of experience can earn between 8-12 lakhs per annum.

Machine learning has defined the way in which businesses grow and interact with customers; however, its application is not limited to business alone. The sheer abundance of data and the need of personalisation has made machine learning a desired skill in almost every professional role. In a world which is increasingly being driven by data, machine learning is the perfect solution for anyone who wishes to stay relevant in their field.

Tags: careerML NewsPython
Share7Tweet3Share1Pin1
Shreya pandey

Shreya pandey

Related Posts

How Machine Learning and Artificial Intelligence helping traders or Stock Market
Machine Learning

How Machine Learning and Artificial Intelligence helping traders/Stock Market

September 20, 2020
How Machine Learning help to Value your Business
Machine Learning

Top 12 Reason How Machine Learning Grow Your Business Value

September 12, 2020
Fraud Prevention with ML in eCommerce – Main Treats and the Ways to Do It
Machine Learning

Fraud Prevention with ML in eCommerce – Main Treats and the Ways to Do It

April 27, 2020
Machine learning Covid-19
Machine Learning

What Researches says on Machine learning with COVID-19

March 27, 2020
Diversity in Training Dataset to Cater Gender Bias in Machine Learning Models
Machine Learning

Diversity in Training Dataset to Cater Gender Bias in Machine Learning Models

January 23, 2020
How to Detect human diseases using radiographs on machine learning models?
Machine Learning

How to Detect human diseases using radiographs on machine learning models?

December 10, 2019

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

I agree to the Terms & Conditions and Privacy Policy.

Latest Stories

Paid VS Organic Online Traffic: Why you should use them in tandem? 2
Marketing Trends

Paid VS Organic Online Traffic: Why you should use them in tandem?

by Sony T
January 25, 2021
Alibaba Cloud Computing Now Ranked Third-Largest Infrastucture as a Service Provider
Cloud Computing

Alibaba Cloud Computing Now Ranked Third-Largest Iaas Provider

by Srikanth
January 25, 2021
How a SERP Checker Can Improve Your Search Rankings
Marketing Trends

How a SERP Checker Can Improve Your Search Rankings

by Srikanth
January 23, 2021
Meet India’s Atmanirbhar Microprocessor chip ‘Moushik’, meant for IoT devices
Internet Of Things

Meet India’s Atmanirbhar Microprocessor chip ‘Moushik’, meant for IoT devices

by Srikanth
January 22, 2021
Bolo Indya
Startup news

Bolo Meets is helping content creators by monetizing their content

by Sony T
January 22, 2021
Load More
Techiexpert.com

© 2020 All Rights Reserved

  • Terms of use
  • Privacy Policy
  • About Us
  • Contact us
  • Write For Us
  • Cookie Policy

  • Login
  • Sign Up
No Result
View All Result
  • Home
  • Tech news
  • Startups
  • AI
  • IOT
  • Big Data
  • Cloud
  • Data Analytics
  • ML
  • Blogging

© 2020 All Rights Reserved

Welcome Back!

Login to your account below

Forgotten Password? Sign Up

Create New Account!

Fill the forms below to register

*By registering into our website, you agree to the Terms & Conditions and Privacy Policy.
All fields are required. Log In

Retrieve your password

Please enter your username or email address to reset your password.

Log In
This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy and Cookie Policy.