Ke Your Own Neural Network in PythonA step by step visual journey through the mathematics of neural networks and making your own using Python and TensorflowWhat you will gain from this bookA deep understanding of how a Neural Network worksHow to build a Neural Network from scratch using PythonWho this book is forBeginners who want to fully understand how networks work and learn to build two step by step examples in PythonProgrammers who need an easy to read but solid refresher on the math of neural networksWhats Inside Make Your Own Neural Network An Indepth Visual Introduction For BeginnersWhat Is a Neural Network?Neural networks have made a gigantic comeback in the last few decades and you likely make use of them everyday without realizing it but what exactly is a neural network? What is it used for and how does it fit within the broader arena of machine learning?we gently explore these topics so that we can be prepared to dive deep further on To start well begin with a high level overview of machine learning and then drill down into the specifics of a neural networkThe Math of Neural NetworksOn a high level a network learns just like we do through trial and error This is true regardless if the network is supervised unsupervised or semi supervised Once we dig a bit deeper though we discover that a handful of mathematical functions play a major role in the trial and error process It also becomes clear that a grasp of the underlying mathematics helps clarify how a network learns Forward Propagation Calculating The Total Error Calculating The Gradients Updating The WeightsMake Your Own Artificial Neural Network Hands on ExampleYou will learn to build a simple neural network using all the concepts and functions we learned in the previous few chapters Our example will be basic but hopefully very intuitive Many examples available online are either hopelessly abstract or make use of the same data sets which can be repetitive Our goal is to be crystal clear and engaging but with a touch of fun and uniueness This section contains the following eight chaptersBuilding Neural Networks in PythonThere are many ways to build a neural network and lots of tools to get the job done This is fantastic but it can also be overwhelming when you start because there are so many tools to choose from We are going to take a look at what tools are needed and help you nail down the essentials To build a neural networkTensorflow and Neural NetworksThere is no single way to build a feedforward neural network with Python and that is especially true if you throw Tensorflow into the mix However there is a general framework that exists that can be divided into five steps and grouped into two parts We are going to briefly explore these five steps so that we are prepared to use them to build a network later on Ready? Lets beginNeural Network Distinguish HandwritingWe are going to dig deep with Tensorflow and build a neural network that can distinguish between handwritten numbers Well use the same 5 steps we covered in the high level overview and we are going to take time exploring each line of codeNeural Network Classify Images10 minutes Thats all it takes to build an image classifier thanks to Google We will provide a high level overview of how to classify images using a convolutional neural network CNN and Googles Inception V3 model Once finished you will be able to tweak this code to classify any type of image sets Cats bats super heroes the skys the limit.

report kindle issue free Report an free Report an issue PDF/EPUBKe Your Own Neural Network in PythonA step by step visual journey through the mathematics of neural networks and making your own using Python and TensorflowWhat you will gain from this bookA deep understanding of how a Neural Network worksHow to build a Neural Network from scratch using PythonWho this book is forBeginners who want to fully understand how networks work and learn to build two step by step examples in PythonProgrammers who need an easy to read but solid refresher on the math of neural networksWhats Inside Make Your Own Neural Network An Indepth Visual Introduction For BeginnersWhat Is a Neural Network?Neural networks have made a gigantic comeback in the last few decades and you likely make use of them everyday without realizing it but what exactly is a neural network? What is it used for and how does it fit within the broader arena of machine learning?we gently explore these topics so that we can be prepared to dive deep further on To start well begin with a high level overview of machine learning and then drill down into the specifics of a neural networkThe Math of Neural NetworksOn a high level a network learns just like we do through trial and error This is true regardless if the network is supervised unsupervised or semi supervised Once we dig a bit deeper though we discover that a handful of mathematical functions play a major role in the trial and error process It also becomes clear that a grasp of the underlying mathematics helps clarify how a network learns Forward Propagation Calculating The Total Error Calculating The Gradients Updating The WeightsMake Your Own Artificial Neural Network Hands on ExampleYou will learn to build a simple neural network using all the concepts and functions we learned in the previous few chapters Our example will be basic but hopefully very intuitive Many examples available online are either hopelessly abstract or make use of the same data sets which can be repetitive Our goal is to be crystal clear and engaging but with a touch of fun and uniueness This section contains the following eight chaptersBuilding Neural Networks in PythonThere are many ways to build a neural network and lots of tools to get the job done This is fantastic but it can also be overwhelming when you start because there are so many tools to choose from We are going to take a look at what tools are needed and help you nail down the essentials To build a neural networkTensorflow and Neural NetworksThere is no single way to build a feedforward neural network with Python and that is especially true if you throw Tensorflow into the mix However there is a general framework that exists that can be divided into five steps and grouped into two parts We are going to briefly explore these five steps so that we are prepared to use them to build a network later on Ready? Lets beginNeural Network Distinguish HandwritingWe are going to dig deep with Tensorflow and build a neural network that can distinguish between handwritten numbers Well use the same 5 steps we covered in the high level overview and we are going to take time exploring each line of codeNeural Network Classify Images10 minutes Thats all it takes to build an image classifier thanks to Google We will provide a high level overview of how to classify images using a convolutional neural network CNN and Googles Inception V3 model Once finished you will be able to tweak this code to classify any type of image sets Cats bats super heroes the skys the limit.