i have been in this DS for over decade and did some work on NN's and come along with Deep Leaning and people started ask this how easy and difficult is this after all you just train a nets with some data, (dont get into that linear or non) all we do is to put that one algo and train and wait , so what is so difficult of it, dont tell me it complex, before use this word , tell me what is complex of have you invented anything or framework no, 99.9 we are just using these technologies that some brought our plate , given this how difficult or easy this deep learning and data science on whole
Deep machine learning will remain so as long as there are those who refer to it without understanding its algorithms, and at the same time there are those who are experts in it.
there is nothing like expert , since you have no role in bring that context no can call as expert coming to and sir "algorithms" are as they, it in context of data how good it is, since there is not single algo developed for your Deep...
all of which are used pre 1980, not even single one developed for this and sir if you any algo that is developed after the deep ... come to foray please let me
The perception that deep learning and data science are easy is misguided. While it is true that many of the tools and frameworks used in these fields are readily available and accessible, the process of designing and training effective models is still highly complex and requires a deep understanding of mathematical concepts, programming skills, and a solid understanding of the underlying data.
The difficulty lies in the design of the model architecture, selection of appropriate hyperparameters, preprocessing and cleaning of data, and interpretation of results. The process of training a deep learning model can be time-consuming, and the risk of overfitting or underfitting is high. The field is rapidly evolving, and keeping up with the latest advancements and techniques requires continuous learning and adaptation.
In short, while it may appear that deep learning and data science are easy because of the tools and frameworks available, it is important to remember that the process of designing and implementing effective models requires significant expertise and effort.
any tool have you developed , what you said all you are just using and what is matter with it after all you do that and in the end you get the probabilities
9.8 m/s^2 what newton arrived at did he has all these , from then have we have created that said that ok this for future, million time in my 30 years technology no ever showed me this is really complex , in first place what is complex look at of the CERN project they are working on this data thing even before your Dee... was there , do you mean Deep changed the way we thing right brothers used only used two metrics one fuel and altimeter yet they flown , in Boeing you have 1800 metrics are there , have reduced the fuel consumption
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