I used to think Deep Learning is difficult before even learning the concept of
neural networks.
3 months into and I can confidently say that it's no different from classical
machine learning.

*Now technicals*
Models such as linear regression, logistic regression, SVMs etc. are trained on
their coefficients, i.e. the training task is to find the optimal values of the
coefficients to minimize some cost function.

Guess what? Neural networks are no different! They are trained on weights and
biases.

During training, the neural network learning algorithm fits various models to
the training data and selects the best model for prediction. The learning
algorithm is trained with a fixed set of hyperparameters - the network structure
(number of layers, number of neurons in the input, hidden and output layers
etc.). It is trained on the weights and the biases, which are the parameters of
the network.

#deeplearning #machinelearning #datascience #learndatascience #neuralnetworks
#classification #artificialintelligence #bigdata #analytics



Posted by Suraaj Hasija on LinkedIn
link: linkedin.com/in/suraajhasija