| from flask import Flask | |
| app = Flask(__name__) | |
| @app.route('/') | |
| def hello_world(): | |
| return "Hello World!" | |
| app.run(debug=True) |
| // Use Gists to store code you would like to remember later on | |
| console.log(window); // log the "window" object to the console |
by Jay Baxter (circa 2009)
"This list is for people who want to become Associate Software Engineers at Blizzard. An associate should have skills at the level indicated by these books. Note that this is almost completely focused on C++ programming. This list is incomplete. I need a book on how to become a professional. I've listed several books that give examples of professional behavior, but not one on the actual training."
by Bjarne Stroustrup
A collection of case studies, white papers, articles, books, and other resources to help prepare you for a Google Cloud Platform certification or two.
If you interested in a particular topic, a good place to start is the Tutorials and Solutions section of cloud.google.com. Search by keyword or browse around. Otherwise, I've currated some of the articles I think would be helpful and added t
| from bson.objectid import ObjectId | |
| from flask_pymongo import PyMongo | |
| builtin_list = list | |
| workflow_builtin_list = list | |
| mongo = None | |
| # Defining the sigmoid function for activations | |
| def sigmoid(x): | |
| return 1/(1+np.exp(-x)) | |
| # Derivative of the sigmoid function | |
| def sigmoid_prime(x): | |
| return sigmoid(x) * (1 - sigmoid(x)) | |
| # Input data | |
| x = np.array([0.1, 0.3]) |
| admit | gre | gpa | rank | |
|---|---|---|---|---|
| 0 | 380 | 3.61 | 3 | |
| 1 | 660 | 3.67 | 3 | |
| 1 | 800 | 4 | 1 | |
| 1 | 640 | 3.19 | 4 | |
| 0 | 520 | 2.93 | 4 | |
| 1 | 760 | 3 | 2 | |
| 1 | 560 | 2.98 | 1 | |
| 0 | 400 | 3.08 | 2 | |
| 1 | 540 | 3.39 | 3 |
| import numpy as np | |
| def sigmoid(x): | |
| """ | |
| Calculate sigmoid | |
| """ | |
| return 1/(1+np.exp(-x)) | |
| # Network size | |
| N_input = 4 |
| import numpy as np | |
| def sigmoid(x): | |
| """ | |
| Calculate sigmoid | |
| """ | |
| return 1 / (1 + np.exp(-x)) | |
| import numpy as np | |
| from data_prep import features, targets, features_test, targets_test | |
| np.random.seed(21) | |
| def sigmoid(x): | |
| """ | |
| Calculate sigmoid | |
| """ | |
| return 1 / (1 + np.exp(-x)) |
