About the Book
What's the first thing that comes to your mind when you think of machine learning?
And you start thinking, I need a PhD in 10 different disciplines just to get started with this!
But what if machine learning wasn't so hard? What if you could build your own Neural Network from scratch, using basic Python?
Introducing Neural Networks
Neural Networks are machine learning algorithms loosely modeled on the human brain. They are great at solving complex problems like image recognition and speech processing.
Even though Neural Networks can solve complex problems, their implementation is fairly easy, and only uses high school level maths (and if even that scares you, I will cover all the maths required with examples).
To reiterate: We will be using very little maths. The focus will be on practical stuff.
What we will go over in this eBook:
1. Theory behind Neural Networks
2. A simplified intro to the maths behind neural networks
3. Back propagation, multiple layers and more
4. A complex example, like recognise handwritten digits
- Introduction to Keras
- Carry out Sentiment analysis on movie reviews
- Build your own image detector, recognise images like cars, ships and different animals etc
About the Author
Shantnu trained as an Electronics Engineer, and spent several years working with low level code, including DSPs, embedded systems and embedded Linux.
Soon, he grew disillusioned by fixing dangling pointers, memory leaks, race conditions, bugs which only appeared once every two weeks.
In desperation, Shantnu threw up his hands and said, “Lord! Is there more than life to this?”
And that night, SpongBob SquarePants appeared in his dream. “My son,” he said, “try Python. It will fix all your problems.”
And Shantnu did, and lo! All was well.
And now, Shantnu is sharing the love…