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I am doing my project in computational neuroscience and I have to make the cerebellar network for that. I made neuron cells code in python like Purkinje cell, Golgi cell. Can you please help me how should I start connecting the neuron cells or making the layers like granular layer and molecular layer in cerebellum?
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Hi Zahid, thanks for the compliment! We will definitely look into your suggestions. Do check out our other videos also and stay tuned for future updates. Cheers!
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Great starter. It seem that a great video would be a one where the data is a row of numbers with one or two output values (from say a cvs file). The concept of a relative need of normalizing the numbers (or not) prior to being taken into the network and testing the performance of the network using a percentage of the data rows. Also, the concept of preforming modifications to the amount of hidden layers and finding/selecting those hidden layer compositions that provide better performance. Then given the network is at the performance level, how you create a brand new row and run/get the results of what the projected answer(s) are. Also, provide a discussion of whether the input of a lot of raw data can be enhanced by attempting to determine if specific math functions would be helpful in helping the network gleam the underlying physics of a set of data. Also, if data is artificially being somewhat manipulated by random increase/decrease over random time, is there a feature of the NNs that tell the amount of random inputs the process received if the data captures the data over time and provides a look back (a few values) in each row. It seems like a lot of discussions are getting away from the simple concept that armatures have of creating data and trying to predict and future event. Again thanks for providing this look at the subject from what python can now provide. I was raised on Basic, Fortran and Machine Language and so this is very interesting to see how language has captured features of a lot of programming in a single string/vocabulary by ganging extremely relevant words together.
Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
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Got a question on the topic? Please share it in the comment section below. For Edureka NIT PGP in Machine Learning and AI Curriculum, Visit our Website: bit.ly/2uUxVjr Use code *_RUclips20_* for exclusive discounts.
Hey! Nice video
So had a query: can we predict for missing input values here? for example i want the output for [2,4], so is it possible?
You really know how to explain your stuff, great video!
We are super happy that Edureka is helping you learn better. Your support means a lot to us and it motivated us to create even better learning content and courses experience for you . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
hello sir i want to calculate weights and bais for last hidden layer which can be used for calculation of output layer please help me
I am doing my project in computational neuroscience and I have to make the cerebellar network for that. I made neuron cells code in python like Purkinje cell, Golgi cell. Can you please help me how should I start connecting the neuron cells or making the layers like granular layer and molecular layer in cerebellum?
I love edurekha it is best website for code learning
Suppose i want a classification model and my classes are very identical to each other so to get accurate result should I use more hidden layers?
Can you explain identifying fake profiles use of artificial neural networks with python?
Thanks very much. your information enrich my knowledge significantly.
Hey:) Thank you so much for your sweet words :) Really means a lot ! Glad to know that our content/courses is making you learn better :) Our team is striving hard to give the best content. Keep learning with us -Team Edureka :) Don't forget to like the video and share it with maximum people:) Do subscribe the channel:)
It was a nice content as usual. If possible, can you guys make videos on Julia language as well.
Hi Zahid, thanks for the compliment! We will definitely look into your suggestions. Do check out our other videos also and stay tuned for future updates. Cheers!
Very informative video
Hey Snehal, thanks for the compliment!
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can we build our own algorithm and can we stabilize algorithm or combine???
thanks a lot for the video
You are welcome :) Keep learning with us...
Thanks for tutoroal
Very helpful ... thank-you
hi, im just begin using pythoon because id like to know how many trees are in a picture, but is hard to implement, thanks for your assistance
Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
Great starter. It seem that a great video would be a one where the data is a row of numbers with one or two output values (from say a cvs file). The concept of a relative need of normalizing the numbers (or not) prior to being taken into the network and testing the performance of the network using a percentage of the data rows. Also, the concept of preforming modifications to the amount of hidden layers and finding/selecting those hidden layer compositions that provide better performance. Then given the network is at the performance level, how you create a brand new row and run/get the results of what the projected answer(s) are. Also, provide a discussion of whether the input of a lot of raw data can be enhanced by attempting to determine if specific math functions would be helpful in helping the network gleam the underlying physics of a set of data. Also, if data is artificially being somewhat manipulated by random increase/decrease over random time, is there a feature of the NNs that tell the amount of random inputs the process received if the data captures the data over time and provides a look back (a few values) in each row. It seems like a lot of discussions are getting away from the simple concept that armatures have of creating data and trying to predict and future event. Again thanks for providing this look at the subject from what python can now provide. I was raised on Basic, Fortran and Machine Language and so this is very interesting to see how language has captured features of a lot of programming in a single string/vocabulary by ganging extremely relevant words together.
Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
Neural Network model to predict sales amount or customer predictions please tell !!!!!
Can you please share the code?
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Very helpful video
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