How to Become a Machine Learning Engineer? - PowerPoint PPT Presentation

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How to Become a Machine Learning Engineer?


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. – PowerPoint PPT presentation

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Title: How to Become a Machine Learning Engineer?

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.
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
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
Data Science Vs Machine Learning
Industry Trends and Future Scope of Machine
  • 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.
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.
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.
Companies Hiring Machine Learning Engineers
As per
  • 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
New York
Different Roles Offered in the Area of Machine
  1. Machine Learning Engineer Machine Learning
    Engineers create AI-based solutions that let
    machines to perform certain tasks without human
  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.
Different Roles Offered in the Area of Machine
  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.
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.
Roles and Responsibilities of a Machine Learning
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
  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.
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
  • The top 3 industries offering highest salary
    packages to the candidates are Consumer Goods,
    Hardware Networking, and Software IT
  • 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.
Prerequisites to Become a Machine Learning
Begin with learning  Python for Beginners
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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
  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.

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