Work On Machine Learning Project Car Price Prediction


  • basic knowledge of machine learning


Video surveillance, traffic alerts on your smartphones, facial recognition software, personalized product recommendations as you browse a website these are all examples of real-life machine learning applications.

This vitally important field, a subdiscipline of artificial intelligence, is attracting a lot of attention lately — both for its technological breakthroughs and lucrative career opportunities. Employment website Indeed has listed machine learning engineer as #1 among The Best Jobs in the U.S. , citing a 344% rate of growth and a median salary of $146,085 per year.

Overall, computer and information technology jobs are booming, with employment projected to grow 11% from 2019 to 2029. More specifically, the Future of Jobs Report 2020 predicts that artificial intelligence will create 12 million new jobs across 26 countries by 2025 (representing a net gain — 97 million new jobs created while 85 million are displaced).

With high demand for AI and machine learning talent driving high salaries, the majority of machine learning jobs pay well over $100,000 with some, such as machine learning engineer, paying up to $200,000.

There are several types of machine learning professionals, and job responsibilities may overlap with other roles, depending on the size of an organization, Roles like Machine Learning Engineer, Data Science Engineer, Data Scientist, ML Developer etc. In general, machine learning deals with complex challenges.

In this course we are going to work on Building a Machine Learning Project on Car Price Prediction.

Steps to Complete a Machine Learning Project are

  1. Collecting Data: As you know, machines initially learn from the data that you give them
  2. Preparing the Data: After you have your data, you have to prepare it
  3. Choosing a Model
  4. Training the Model
  5. Evaluating the Model
  6. Parameter Tuning
  7. Making Predictions

If you are beginner in the field of machine learning, enroll the course to learn latest ML methods.

Who this course is for:

  • Beginners in machine learning
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