Hello Everybody!
Hello Eaverybody!start a discussion about some important concepts as many postgraduates students have some confusion about it. In simple expression
Machine Learning = Data + Algorithms
In your opinion which one is more important; data or algorithms?
Greetings,
I wouldndare to say algorithms. It would be keep it simple, data is everywhere just need to take it, but algoritms not, good one sure not.
Hope I helped a bit.
Greetings,
I must say both are equally important but now we have machine learning algorithm that are not driven by data. We call them unsupervised learning techniques. So here the importance of algorithm increases by a fare amount.
Data... because "It's not who has the best algorithm that wins,It's who has the most data" - andrew ng
"The World is one big data problem." - Andrew McAfee.
Thanks for participation, ML depends heavily on data, without data, it is impossible for any algorithm to learn. It is the most crucial aspect that makes algorithm training possible… No matter how great your ML product is. If your data set is not good enough, your entire project will fail! I have seen fantastic projects fail because we didn’t have a good data set despite having the perfect use case and very skilled data scientists and great algorithms.
Machine learning - algorithm is more appropriate as it is algo which plays which plays with data. The learning process is governed by the algorithm.
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