Ever since the companies have realized that the regular software are not going to address the growing competition and that they need something additional to pull them, concepts like Data Science and Machine Learning have started gaining momentum. Whether it is Voice Recognition based searching, Fraud Detection Systems, or a Recommendation System by Amazon or Netflix, Machine Learning has been the most implemented technology over the period of time.

1. www.simpliv.co

2. “Machine Learning is the field that is a subset of
Artificial Intelligence, is a process that deals with
educating a computer system so that it learns from
its own feedback, instead of having to explicitly
program it for every task.”
What is
Machine Learning?
www.simpliv.co

3. Applications of Machine Learning
www.simpliv.co
1. Image Recognition: Identifying objects like persons, places, etc., on the images
are done using Machine Learning Techniques.
2. Virtual Assistance: Various Virtual Assistance Systems like Cortana, Siri, Alexa
recognize and respond to Natural Language using Machine Learning Algorithms.
3. Email Spam and Malware Filtering: Whenever a suspicious mail arrives it lands
on Spam folder. Any mail that violates the filtering rules, Machine Learning
Algorithms push them to junk folder.

4. Applications of Machine Learning
www.simpliv.co
4) Self-driving Cars: Companies like Google and Tesla are manufacturing Driverless
cars that do not require human drivers. This is done by Machine Learning and
Deep Learning Algorithms that help Cars to make decisions like humans.
5) Speech Recognition: Various Virtual Assistance Systems like Cortana, Siri, Alexa
recognize and respond to Natural Language using Machine Learning Algorithms.
6) Automatic Language Translation: Similar to Speech Recognition, Automatic
Language Translation deals with Natural Language Processing and works on
Machine Learning Algorithms.
READ MORE
Get your fundamentals of
Machine Learning with the blog:

5. Data Science Vs Machine Learning
www.simpliv.co

6. Industry Trends and Future Scope of
Machine Learning
www.simpliv.co
• As per Gartner published a Hype Cycle for Artificial Intelligence 2019, technologies
like Adaptive Machine Learning, Edge AI, Edge Analytics, Graph Analytics,
Autonomous Driving Level 4 &5, etc., are have quite a bright future in the span of 2
to 10 years.
• As per Statista, the cumulative funding for AI worldwide is highest $28.5 Billion in
Machine Learning Applications.
• As per Market Research Future, the Global Machine Learning Market is expected to
expand at 42.08% CAGR during the forecast period 2018–2024.

7. Role of Machine Learning in Business
www.simpliv.co
1. Financial Services: Various financial institutes use Machine Learning for various
purposes. The two major applications are Fraud Detection and Stock Market
Trading.
2. Healthcare: Machine Learning has given ways to Diagnose and Treat the Patients
with utmost accuracy and security, and also to Anticipate the Future Health
Conditions.
3. Retail: Machine Learning is used in Retaining for Product Recommendation,
Managing Inventory Level, Formulating Routing Strategies, and Anticipating
Product Demand.

8. Role of Machine Learning in Business
www.simpliv.co
4. Manufacturing: Manufacturing firms are also utilizing Machine Learning Techniques
for General Process Improvement, Product Development, Quality Control, and
much more.
5. Transportation: Machine Learning has given a whole new dimension to the
Transportation Industry through Real-time Location Updates and Real-time Traffic
Updates.
6. Oil and Gas: Some of the major ways Machine Learning is helping Oil and Gas
industry are Accurate Modeling and Drilling Automation.

9. Companies Hiring Machine Learning Engineers
www.simpliv.co
• The top 3 companies paying the highest to Machine Learning Engineers are Selby Jennings, Twitter, and DoorDash.
As per Indeed.com:
• The top 3 locations in U.S. that are the melting pots for Machine Learning Engineers are San Francisco, Bellevue, and
New York.
San Francisco Bellevue New York

10. Different Roles Offered in the Area of Machine Learning
www.simpliv.co
1. Machine Learning Engineer: Machine Learning Engineers create AI-based
solutions that let machines to perform certain tasks without human intervention.
2. Data Scientist: Data Scientists are the professionals who wrangle with the data to
solve a business problem.
3. NLP Scientist: NLP stands for ‘Natural Language Processing’. NLP Scientists
develop machines that are able to understand the natural language and translate
it into other spoken languages.

11. Different Roles Offered in the Area of Machine Learning
www.simpliv.co
4. Business Intelligence Developer: A Business Intelligence Developer can be
understood as the professional who collects, analyzes, and interprets huge
amounts of data in order to draw actionable insights that can be used to solve
a business issue.
5. Human-Centered Machine Learning (HCML) Developer: A Human-Centered
Machine Learning Developer is a professional who is responsible for
developing systems that can process the information based on Human-based
Machine Learning Algorithms and recognize the patterns.

12. Who is Machine Learning Engineer?
www.simpliv.co
A Machine Learning Engineer can be defined as a professional who ensures that the
models developed by Data Scientists are running without obstacles and producing
accurate information at the right time.
For an instance, Machine Learning Engineers’ job is to design the programming so
that the search results fetch the appropriate results.

13. Roles and Responsibilities of a Machine Learning Engineer
www.simpliv.co
A Machine Learning Engineer is responsible for carrying out following jobs:
1. Develop the models that have the potential to improve the machine learning
systems.
2. Monitor and expand the models, build the datasets and streamline the
parameters to accelerate the system performance.
3. Develop software that can improve the experimentation and allows making
better business decisions.
4. Build the tools for analysis and simulations that can understand the process of
complex systems.
5. Apply Machine Learning techniques to resolve new and critical areas.

14. Salary of a Machine Learning Engineer
www.simpliv.co
As per LinkedIn:
• There are 6,650 Job Posts for Machine Learning Engineers only in the U.S.
• The Median Salary or the Average Salary drawn by the Machine Learning
Engineers is $1,25,000 annually.
• The top 3 industries offering highest salary packages to the candidates are
Consumer Goods, Hardware & Networking, and Software & IT Services.
• The top 3 locations hiring Machine Learning Exerts in highest packages are San
Francisco Bay Area, Greater Seattle Area, and New York City Metropolitan Area.

15. Prerequisites to Become a Machine Learning Engineer
www.simpliv.co
Begin with learning
Python for Beginners course and increase the
chances of your selection in one shot! Explore the
curriculum here!

16. Learning Path for Machine Learning Engineer
www.simpliv.co
1. Learning the Skills: Someone who wishes to become a Machine Learning
Engineer should get a Master’s Degree or Ph.D. in computer science and
engineering as merely getting a Bachelor’s degree will not suffice.
2. Gaining Experience: Platforms like Github and Kaggle work best for
freelancer Machine Learning professionals.
3. Acquiring a Job: If you are a fresh graduate, there are more chances that you
will get a position of Junior-level Machine Learning Engineer will be expected
to work on the applications and data wrangling activities.
This course for Artificial Intelligence and Machine Learning is just the right
package for Data Science aspirants to land a high-paying job in no time.

17. Start Your Certification Journey with
SIMPLIV NOW!
Visit at
www.simpliv.com
to LEARN MORE!
Explore Blogs:
blog.simpliv.com
For queries:
USA: +510 849 6155