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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.

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How to Become a Machine Learning Engineer?

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  1. www.simpliv.com

  2. 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.” www.simpliv.com

  3. Applications of Machine Learning Image Recognition:Identifying objects like persons, places, etc., on the images are done using Machine Learning Techniques. Virtual Assistance: Various Virtual Assistance Systems like Cortana, Siri, Alexa recognize and respond to Natural Language using Machine Learning Algorithms. 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. www.simpliv.com

  4. Applications of Machine Learning 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. Speech Recognition: Various Virtual Assistance Systems like Cortana, Siri, Alexa recognize and respond to Natural Language using Machine Learning Algorithms. 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: READ MORE www.simpliv.com

  5. Data ScienceVsMachine Learning www.simpliv.com

  6. 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 Billionin 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. www.simpliv.com

  7. Role of Machine Learning in Business • Financial Services:Various financial institutes use Machine Learning for various purposes. The two major applications are Fraud Detection and Stock Market Trading. • 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. • Retail:Machine Learning is used in Retaining for Product Recommendation, Managing Inventory Level, Formulating Routing Strategies, and Anticipating Product Demand. www.simpliv.com

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

  9. 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 www.simpliv.com

  10. Different Roles Offered in the Area of Machine Learning • Machine Learning Engineer: Machine Learning Engineers create AI-based solutions that let machines to perform certain tasks without human intervention. • Data Scientist: Data Scientists are the professionals who wrangle with the data to solve a business problem. • 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. www.simpliv.com

  11. Different Roles Offered in the Area of Machine Learning • Business Intelligence Developer: ABusiness 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. • 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. www.simpliv.com

  12. 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. www.simpliv.com

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

  14. 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. www.simpliv.com

  15. 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! www.simpliv.com

  16. Learning Path for Machine Learning Engineer • 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. • Gaining Experience: Platforms like Github and Kaggle work best for freelancer Machine Learning professionals. • 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. www.simpliv.com

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

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