Today's learning :-
- It was a day of learning ML and python both, started with quick revision and then started Deep learning. Since lazy execution and graphs are the bash of DL.
- Sklearn(Sci-kit Learn) which use numpy in background doesn't support lazy execution and graphs hence we need a new type of data type which support both both of these.
- For this we have a new data type Tensor which comes from TensorFlow module but directly we don't use TensorFlow as well.
- For this we have a new approch which is known as Keras.
- As humans has neural network in human brain, we can create same kind of neural network in using computer programming to enable computer think like human which makes it intelligent.
- Neurons and nodes which receive input from input nodes (features). Neurons decide the weightage of every input and then send it to another neuron which eliminates the features on the basis of function provided in it.
- This neuron is known as activation function and then it gives the output. This complete process is known as Artificial Neural Network (ANN).
- Features are in the input layer, output is in output layer and the whole ANN operates in Hidden Layer. If Hidden Layer => 3, then that network is known as deep net and the learning by this network is known as Deep learning.
- When we have one neuron it is known as.
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