- Stand up straight with your shoulders back: man up, we are all on this Earth to suffer.
- Treat yourself like someone you are responsible for helping: Stop waiting for other people to dig you out of your pitiful hole.
- Make friends with people who want the best for you: If people are determined to screw up, let them they will drag you down to their level. So stick with the winners.
- Compare yourself to who you were yesterday, not to who someone else is today: Happiness is the PROGRESS for winning. Winning itself doesnt mean that much. Dont compare yourself with the smartest man on earth.
- Do not let your children do anything that makes you dislike them:
- Set your house in perfect order before you criticize the world
- Pursue what is meaningful (not what is expedient): So quit looking for short cuts and start reading Nietzsche.
- Tell the truth – or, at least, don't lie
Instead of implementing a single algorithm directly, code receives run-time instructions as to which in a family of algorithms to use. It helps reducing the amount of inheritance needed. Instead of creating a multi level convoluted inheritance to share code, you can use Strategy to reduce code complexity and share code across siblings.
@FunctionalInterface
interface BillingStrategy {
// use a price in cents to avoid floating point round-off error
Type | Complexity | Weights per layer | Sequential Operations |
---|
Summary of : https://medium.com/free-code-camp/microservices-from-idea-to-starting-line-ae5317a6ff02
- Cohesion and coupling is traditionally the technical debt grasping onto our feet, slowing us down.
- Complexity comes from low cohesion and high coupling. Microservices provides the structure to keep that at bay.
- Benefits can include horizontal scalability, testability, reliability, observability, replaceability, and language independence.
- The downside for microservices is that to achieve these benefits, you must provide an underlying infrastructure which supports them. Without that support, you can easily find yourself with an unreliable and opaque system — or you find yourself reinventing the reliability wheel in every single service.
List of Useful Links to Best Understand MEL/MFCC Generation:
- Overview on the process: https://haythamfayek.com/2016/04/21/speech-processing-for-machine-learning.html
- Spectral Leakage and Zero Padding: https://dspillustrations.com/pages/posts/misc/spectral-leakage-zero-padding-and-frequency-resolution.html
- MEL Visualization: http://practicalcryptography.com/miscellaneous/machine-learning/guide-mel-frequency-cepstral-coefficients-mfccs/
- For signal live illustrations: https://jackschaedler.github.io/circles-sines-signals/
- How to select
n
when doing MEL spectrum: https://dsp.stackexchange.com/questions/37946/confusion-in-n-of-n-point-fft
Loss functions is a method of evaluating how well specific algorithm models the given data. If predictions deviates too much from actual results, loss function will compute a large positive number. Gradually, with the help of some optimization function, the model will make better predictions and reduce overall loss.
The cost function is the average of the losses. You first calculate the loss, one for each data point, based on your prediction and your ground truth label. Then, you average these losses which corresponds to your cost.