Today's Progress: Fixed CSS, worked on canvas functionality for the app.
Thoughts: I really struggled with CSS, but, overall, I feel like I am slowly getting better at it. Canvas is still new for me, but I managed to figure out some basic functionality.
| #data storage | |
| import h5py | |
| #matrix math | |
| import numpy as np | |
| #data preprocessing | |
| import pandas as pd | |
| #ETL - Extract, Transform, and Load Data Class | |
| class ETL: |
| #for data loading | |
| import etl | |
| #for machine learning | |
| import keras | |
| #load data | |
| dl = etl.ETL() | |
| #build model | |
| def build_network(layers): |
| #Stock prices | |
| from google_finance import Share | |
| #visualization | |
| from matplotlib import pyplot as plt | |
| #matrix math | |
| import numpy as np | |
| import random | |
| #machine learning | |
| import tensorflow as tf | |
| import random |
| // Step 1 - build Convolutional network | |
| const buildCnn = function (data) { | |
| //A promise represents the eventual result of an asynchronous | |
| //operation. It is a placeholder into which the successful | |
| //result value or reason for failure will materialize. | |
| return new Promise(function (resolve, reject) { | |
| //Linear stack of layers. | |
| const model = tf.sequential() |
| def cross_entropy(X,y): | |
| """ | |
| X is the output from fully connected layer (num_examples x num_classes) | |
| y is labels (num_examples x 1) | |
| """ | |
| m = y.shape[0] | |
| p = softmax(X) | |
| log_likelihood = -np.log(p[range(m),y]) | |
| loss = np.sum(log_likelihood) / m | |
| return loss |
| [ | |
| { | |
| "image_id": "a0f6bdc065a602b7b84a67fb8d14ce403d902e0d", | |
| "human_annotations": | |
| { | |
| "human1": [178,250,290,522], | |
| }, | |
| "keypoint_annotations": | |
| { | |
| "human1": [261, 294, 1, 281, 328, 1, 259, 314, 2, |
| //contract address | |
| var contractAddress = "0x43833c47907be9780581c0fbee97cc6e4f0a99c9"; | |
| //ABI stands for application binary interface. | |
| //In general, an ABI is the interface between two program modules, one of which is often at the level of machine code. | |
| //The interface is the de facto method for encoding/decoding data into/out of the machine code. | |
| //In Ethereum, it's basically how you can encode Solidity contract calls for the EVM and, backwards, | |
| //how to read the data out of transactions. | |
| var ABI = require("./build/contracts/MindMathGame.json").abi; | |
| var web3Host = 'http://localhost'; | |
| var web3Port = '8545'; |
| pragma solidity ^0.4.0; | |
| contract MindMathGame | |
| { | |
| //The blockchain is a list of blocks which are fundamentally lists of transactions. | |
| //Each transaction has an attached receipt which contains zero or more log entries. | |
| //Log entries represent the result of events having fired from a smart contract. | |
| //In the Solidity source code, to define an event, you mark it thus by preceding it with the | |
| //event keyword (similar in usage to the function keyword). You then call or fire the event | |
| //in the body of whatever function you wish to cause to generate the event. |
| from __future__ import print_function | |
| import sys | |
| import vgg, pdb, time | |
| import tensorflow as tf, numpy as np, os | |
| import transform | |
| from utils import get_img | |
| STYLE_LAYERS = ('relu1_1', 'relu2_1', 'relu3_1', 'relu4_1', 'relu5_1') | |
| CONTENT_LAYER = 'relu4_2' | |
| DEVICES = 'CUDA_VISIBLE_DEVICES' |