How much accuracy is good in machine learning?

What Is the Best Score? If you are working on a classification problem, the best score is 100\% accuracy. If you are working on a regression problem, the best score is 0.0 error. These scores are an impossible to achieve upper/lower bound.

Do you need to be good at statistics for machine learning?

Statistics is generally considered a prerequisite to the field of applied machine learning. We need statistics to help transform observations into information and to answer questions about samples of observations.

How good at math do you need to be for machine learning?

For beginners, you don’t need a lot of Mathematics to start doing Machine Learning. The fundamental prerequisite is data analysis as described in this blog post and you can learn the maths on the go as you master more techniques and algorithms.

Is 70 a good accuracy?

If your ‘X’ value is between 70\% and 80\%, you’ve got a good model. If your ‘X’ value is between 80\% and 90\%, you have an excellent model. If your ‘X’ value is between 90\% and 100\%, it’s a probably an overfitting case.

Will machine learning replace statistics?

This is caused in part by the fact that Machine Learning has adopted many of Statistics’ methods, but was never intended to replace statistics, or even to have a statistical basis originally. “Machine learning is statistics scaled up to big data” “The short answer is that there is no difference”

What makes a good machine learning model?

Machine learning model performance is relative and ideas of what score a good model can achieve only make sense and can only be interpreted in the context of the skill scores of other models also trained on the same data. Because machine learning model performance is relative, it is critical to develop a robust baseline.

What are the limitations of machine learning?

Limitation 3 — Data. This is the most obvious limitation. If you feed a model poorly, then it will only give you poor results. This can manifest itself in two ways: lack of data, and lack of good data.

What is machine learning in simple words?

In simple terms, machine learning means using data to train a machine to recognize patterns, and based on those patterns, the machine can make more accurate decisions in the future when presented with new data. Machine learning has various applications such as: Fraud detection: use machine learning…

What can machine learning tell us about normative values?

Clearly, however, machine learning cannot tell us anything about what normative values we should accept, i.e. how we should act in the world in a given situation. As David Hume famously said, one cannot ‘derive an ought from an is’. This is a limitation I personally have had to deal with.