cedrickchee

Inspired by dannyfritz/commit-message-emoji

See also gitmoji.

Commit type	Emoji
Initial commit	🎉 :tada:
Version tag	🔖 :bookmark:
New feature	✨ :sparkles:
Bugfix	🐛 :bug:

cedrickchee

Summary of "Clean Code" by Robert C. Martin

A summary of the main ideas from the "Clean Code: A Handbook of Agile Software Craftsmanship" book by Robert C. Martin (aka. Uncle Bob).

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

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General rules

cedrickchee

This gist was being mentioned by Jeremy in fast.ai deep learning part 2 2018, lesson 9 video. In this lesson, we are learning multi-class object detection (computer vision) using the pascal-multi.ipynb notebook.

One of the fast.ai's students pointed out that by using Pandas, we can do things much simpler than using Python collections.defaultdict and shared this gist.

>The more you get to know Pandas, the more often you realize it is a good way to solve lots of different problems.

cedrickchee

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

cedrickchee

Originally forked from Philipp Bayer's gist. All credits goes to him.

This gist convert the original text to markdown for better readability.

Problems and Ideas:

1. Gene function prediction - given a predicted protein or gene sequence, what is the function?

The classic approach is to use something like BLAST to compare with known sequences, but this has many drawbacks. For starters, in plants the databases lean very heavily towards Arabidopsis thaliana, not more common plants such as maize or wheat.

cedrickchee

cedrickchee

class AMSgrad(Optimizer):
    """AMSGrad optimizer.

    Default parameters follow those provided in the Adam paper.

    # Arguments
        lr: float >= 0. Learning rate.
        beta_1: float, 0 < beta < 1. Generally close to 1.
        beta_2: float, 0 < beta < 1. Generally close to 1.
        epsilon: float >= 0. Fuzz factor.

cedrickchee

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console