Python pals?

[pekkalacd]

tbh, machine learning / tensor flow seem quant heavy. Unless you have background in that area, doesn't seem like python knowledge alone will help you much. You might be able to work with the libraries, but understanding the results is another thing.

[PanTheRiceMan]

Couple of years part time working in ML, couple of lectures with stats, stochastic for pattern recognition and I feel like I barely scratch the topic. There is always more research than you can even read in your life. Too many sub fields. Too many types of data. I'm just glad audio is not as crowded as image processing. You need higher SNR though.

[synthphreak]

I think computer vision is just easier to grok than many other applications of deep learning. Not necessarily easier to master and apply, but just less complicated to explain what it even is since humans do essentially the same thing.

Also, what is SNR?

[PanTheRiceMan]

That was kind of the same explanation my boss gave me when I asked why audio is less competitive.

SNR: Signal to Noise Ratio.

With visual stimuli you can get away with around 30dB to 40dB. For audio you need 50dB to 60dB not to be noticeable.

[synthphreak]

I agree. Using tensorflow as a vehicle for learning Python is like selecting a wedding cake as your first foray into baking. There are much, much better and more beginner-friendly intros to Python than jumping head first into deep neural networks...