Deep Learning with Python

Instead, you will, for sure, have a basic understanding of deep learning and its implications and real-life applications. Most of the time, what confuses us is the application of a certain thing in our lives. Once we know that, we can relate the subject to that particular thing and learn. An interesting thing is that neural networks also learn the same way. This makes it easier to learn about them when we know the basics.
Let's take a look at what this book has to offer:
● The basics of Python including data types, operators and numbers.
● Advanced programming in Python with Python expressions, types and much more.
● A comprehensive overview of deep learning and its link to the smart systems that we are now building.
● An overview of how artificial neural networks work in real life.
● An overview of PyTorch.
● An overview of TensorFlow.
● An overview of Keras.
● How to create a convolutional neural network.
● A comprehensive understanding of deep learning applications and its ethical implications, including in the present and future.
This book offers you the basic knowledge about Python and Deep Learning Neural Networks that you will need to lay the foundation for future studies. This book will start you on the road to mastering the art of deep learning neural networks. When I say that I don't have the magic formula to make you learn, I mean it. My point is that you should learn Python coding and Python libraries to build neural networks by practicing hard. The more you practice, the better it is for your skills. It is only after thorough and in depth practice that you will be able to create your own programs.
Unlike other books, I don't claim that this book will make you a master of deep learning after a single read. That's not realistic, in fact, it's even a bit absurd. What I claim is that you will definitely learn about the basics. The rest is practice. The more you practice the better you code.


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