Is it hard to find a job as a machine learning engineer?

Machine learning is a growing field getting a lot of attention, but getting machine learning jobs is still very difficult. More often than not, there’s a lot of research and learning involved to prepare for applying for a new position.

Can I make money with Kaggle?

Typical Kaggle competition lasts 3 months, offers $25,000-100,000 in prize fund and attracts around 1000 specialists. At least top 10\% of those specialists, ~100 persons are of prime quality, many others ‘just’ good.

Can you earn money on Kaggle?

Is it possible to earn money from Kaggle?

Is it difficult to win Kaggle competition?

It is incredibly difficult to win the top prize at Kaggle challenge. Kaggle lets big companies including the one you are reading now to participate in a contest where the company will put a data set with both training data and confirmation data and some set of clear rules that all teams have to follow.

Will Kaggle help you get a job as a machine learning engineer?

Kaggle does not provide any opportunities to enhance these skills which are also an essential part of getting a job as a Machine Learning engineer. To overcome this flaw, you can apply for machine learning internships that provide a broad understanding of becoming a machine learning engineer. So Will Kaggle Help You Get a job?

What should I know before starting Kaggle as a beginner?

The one thing that you absolutely cannot skip while starting Kaggle is learning a programming language! Python and R are currently the two most famous programming languages for Data Science and Machine Learning.

Does Kaggle help in getting a job?

An excellent Kaggle profile will definitely result in a lot of exposure from recruiters which will help you in getting a job! Performing well on Kaggle demonstrates problem-solving skills and teamwork, which are some characteristics necessary for becoming a good machine learning engineer and help you in standing apart from the crowd.

What are Kaggle micro-courses?

The Micro-Courses (as they are called) start from the basics like Python, Machine Learning, SQL, Data Visualization and move on to more complex topics like Pandas, Deep Learning, Geospatial Analysis, etc. 4. Discussion: There is an entire Discussion section on Kaggle apart from the option of commenting in Notebooks.