There are problems (e.g. this one or this other one) that could potentially be solved easily using traditional algorithmic techniques. I think that training a neural network (or any other machine learning model) for such sorts of problems will be more time consuming, resource-intensive and pointless.

If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Example problems are appreciated.

There are problems (e.g. this one or this other one) that could potentially be solved easily using traditional algorithmic techniques. I think that training a neural network (or any other machine learning model) for such sorts of problems will be more time consuming, resource-intensive, and pointless.

If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Example problems are appreciated.

There are problems (e.g. this one) that could potentially be solved easily using traditional algorithmic techniques (as in coding in your typical programming language. I assume that training a NN (or any other machine learning technique) for such sorts of problems will be more time consuming, resource-intensive and pointless.

If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Example problems are appreciated.

There are problems (e.g. this one or this other one) that could potentially be solved easily using traditional algorithmic techniques. I think that training a neural network (or any other machine learning model) for such sorts of problems will be more time consuming, resource-intensive and pointless.

If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Example problems are appreciated.

So I came across these 2 questions:

• Ideas on how to make a neural net learn how to split sequence into sub sequences
• Search minimum value with learning machine algorithm

For me both problems could be solved easily using traditional algorithmic techniques (as in coding in your typical programming language. I assume that training a NN (or any other machine learning technique) for such sorts of problems will be more time consuming, resource intensive and pointless.

My question is: If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Summary: Choosing between normal computational approach vs abstract approach used in Neural Nets or ML or AI.

Example problems are appreciated :)

There are problems (e.g. this one) that could potentially be solved easily using traditional algorithmic techniques (as in coding in your typical programming language. I assume that training a NN (or any other machine learning technique) for such sorts of problems will be more time consuming, resource-intensive and pointless.

If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

Example problems are appreciated.