Data Science: Deep Learning and Neural Networks in Python free download

What you’ll learn in Data Science: Deep Knowing and also Neural Networks in Python

Learn how Deep Discovering REALLY works (not just some layouts and magical black box code)
Learn just how a semantic network is constructed from standard foundation (the neuron)
Code a neural network from scratch in Python and numpy
Code a semantic network making use of Google’s TensorFlow
Explain various sorts of neural networks as well as the various sorts of troubles they are utilized for
Derive the backpropagation rule from initial principles
Create a semantic network with an outcome that has K > > 2 courses using softmax
Describe the various terms associated with semantic networks, such as “activation”, “backpropagation” as well as “feedforward”
Install TensorFlow

Description

This training course will get you begun in building your FIRST man-made neural network making use of deep discovering methods. Following my previous program on logistic regression, we take this standard foundation, as well as construct full-on non-linear neural networks right out of the gate using Python as well as Numpy. All the materials for this training course are FREE.

We prolong the previous binary category design to numerous classes using the softmax function, and we acquire the very important training method called “backpropagation” using first concepts. I reveal you just how to code backpropagation in Numpy, initially “the sluggish way”, and afterwards “the rapid method” making use of Numpy attributes.

Next off, we carry out a semantic network using Google’s brand-new TensorFlow library.

You must take this program if you are interested in beginning your journey toward coming to be a master at deep learning, or if you are interested in machine learning and also data science as a whole. We go beyond basic versions like logistic regression and also linear regression and I show you something that.