Lots of great comments here already. Just some feedback in the hope that it's useful:
- Assume that your target audience is going to be very eager to learn about DL but have no clue about what exactly to learn or where to even start. That's why they are buying your book in the first place and not some other more dense text.
- Hence, telling your readers what to learn and where to find more info is just as important as the subject matter itself. This can be as easy as e.g. telling the readers about certain keywords that they can use in their Google searches.
- The very best texts that I've read on complicated subjects were always "coarse-to-fine", i.e. give the readers the big picture as early as possible, then enable them to go into details at their own pace.
- Conversely the worst text that I've read on complicated subjects were either fine-to-coarse (trying to explain individual components in detail before going to the big picture), not explaining the big picture at all or being too verbose in the beginning (slowing down the eager readers and killing their motivation). A good example of the latter is Apple's "Programming with Objective-C" [1]. Horrible text IMO.
- Following what was said above sometimes details aren't even necessary to include in your text as long as the readers are confident that they can find their way around and get details elsewhere.
- The very very best texts I've read also always had a motivational component. For someone who's just starting out the field looks vast and un-conquerable and scary. If you show them, in simple words, the boundaries of the field and which areas the experts are working on and even where current research is struggling you help give confidence and trajectory to your readers, so they can strive to become experts too.
Just FYI, there are still a few typos in the sample pdf, I think a spell checker might be useful?
"A neural network learns a function. This might seem confusing since I just told you that it is
a funtion. However, every neural network starts out predicting randomly. In other words, our
starting weight values are random... thus our function predicts randomly. It's a random function.
As you may remember from the previous chapter, a neural network learns how to take
an input dataset and convert it into an output dataset. For example, it might take an input dataset
of Farenheit temperatures and learn to convert it into an output dataset of Celsius temperatures.
It might covert a pixel values dataset"
funtion, Farenheit, covert
Edit:
"We just take each weight... compute its affect on the error... and move it
in the right direction so that the error goes down (to 0)."
- Assume that your target audience is going to be very eager to learn about DL but have no clue about what exactly to learn or where to even start. That's why they are buying your book in the first place and not some other more dense text.
- Hence, telling your readers what to learn and where to find more info is just as important as the subject matter itself. This can be as easy as e.g. telling the readers about certain keywords that they can use in their Google searches.
- The very best texts that I've read on complicated subjects were always "coarse-to-fine", i.e. give the readers the big picture as early as possible, then enable them to go into details at their own pace.
- Conversely the worst text that I've read on complicated subjects were either fine-to-coarse (trying to explain individual components in detail before going to the big picture), not explaining the big picture at all or being too verbose in the beginning (slowing down the eager readers and killing their motivation). A good example of the latter is Apple's "Programming with Objective-C" [1]. Horrible text IMO.
- Following what was said above sometimes details aren't even necessary to include in your text as long as the readers are confident that they can find their way around and get details elsewhere.
- The very very best texts I've read also always had a motivational component. For someone who's just starting out the field looks vast and un-conquerable and scary. If you show them, in simple words, the boundaries of the field and which areas the experts are working on and even where current research is struggling you help give confidence and trajectory to your readers, so they can strive to become experts too.
[1] https://developer.apple.com/library/mac/documentation/Cocoa/...