How to Become a Machine Learning Engineer?

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What is
Machine Learning?
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.
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Applications of Machine Learning

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.

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Applications of Machine Learning

1. 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.
2. Speech Recognition Various Virtual Assistance
   Systems like Cortana, Siri, Alexa recognize and
   respond to Natural Language using Machine
   Learning Algorithms.
3. Automatic Language Translation Similar to Speech
   Recognition, Automatic Language Translation deals
   with Natural Language Processing and works on
   Machine Learning Algorithms.

Get your fundamentals of Machine Learning with
the blog 
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Data Science Vs Machine Learning
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Industry Trends and Future Scope of Machine
Learning

• 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 20182024.

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Role of Machine Learning in Business

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.

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Role of Machine Learning in Business

1. Manufacturing Manufacturing firms are also
   utilizing Machine Learning Techniques for General
   Process Improvement, Product Development, Quality
   Control, and much more.
2. Transportation Machine Learning has given a
   whole new dimension to the Transportation
   Industry through Real-time Location Updates and
   Real-time Traffic Updates.
3. Oil and Gas Some of the major ways Machine
   Learning is helping Oil and Gas industry are
   Accurate Modeling and Drilling Automation.

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Companies Hiring Machine Learning Engineers
As per Indeed.com

• The top 3 companies paying the highest to Machine
  Learning Engineers are Selby Jennings, Twitter,
  and DoorDash.

• 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
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Different Roles Offered in the Area of Machine
Learning

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.

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Different Roles Offered in the Area of Machine
Learning

1. 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.
2. 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.

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Who is Machine Learning Engineer?
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.
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Roles and Responsibilities of a Machine Learning
Engineer
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.

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Salary of a Machine Learning Engineer
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.

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

1. Learning the Skills Someone who wishes to become
   a Machine Learning Engineer should get a Masters
   Degree or Ph.D. in computer science and
   engineering as merely getting a Bachelors 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.
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