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@jthomas
jthomas / package.json
Last active September 24, 2023 21:58
Using TensorFlow.js with MobileNet models for image classification on Node.js
{
"name": "tf-js",
"version": "1.0.0",
"main": "script.js",
"license": "MIT",
"dependencies": {
"@tensorflow-models/mobilenet": "^0.2.2",
"@tensorflow/tfjs": "^0.12.3",
"@tensorflow/tfjs-node": "^0.1.9",
"jpeg-js": "^0.3.4"
@ledmaster
ledmaster / MultipleTimeSeriesForecasting.ipynb
Last active September 24, 2024 15:14
How To Predict Multiple Time Series With Scikit-Learn (With a Sales Forecasting Example)
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# See official docs at https://dash.plotly.com
# pip install dash pandas
from dash import Dash, dcc, html, Input, Output
import plotly.express as px
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv')
@CapCap
CapCap / tensorflow_opencv_ubuntu_deps.sh.txt
Last active January 3, 2023 20:28
Paperspace tensorflow+opencv setup for both python2 and python3 on ubuntu 16
#!/bin/bash
# Don't require you to constantly enter password for sudo:
sudo visudo
# In the bottom of the file, paste the following (without the `#`):
# paperspace ALL=(ALL) NOPASSWD: ALL
# Then press `ctl+o` then `enter` to save your changes, and `ctr+x` to exit nano
# Allow connection from your IP to any port- default seems to be just 22 (ssh)
@leonardofed
leonardofed / README.md
Last active November 22, 2025 14:31
A curated list of AWS resources to prepare for the AWS Certifications


A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.


@jasongilman
jasongilman / atom_clojure_setup.md
Last active October 28, 2025 22:34
This describes how I setup Atom for Clojure Development.

Atom Clojure Setup

This describes how I setup Atom for an ideal Clojure development workflow. This fixes indentation on newlines, handles parentheses, etc. The keybinding settings for enter (in keymap.cson) are important to get proper newlines with indentation at the right level. There are other helpers in init.coffee and keymap.cson that are useful for cutting, copying, pasting, deleting, and indenting Lisp expressions.

Install Atom

Download Atom

The Atom documentation is excellent. It's highly worth reading the flight manual.

@dannguyen
dannguyen / guardian-articles-day-api.md
Last active May 9, 2025 17:24
How to use The Guardian's API to download article data for content analysis (in Python 3.x)

How to use The Guardian's API to download article data for content analysis (in Python 3.x)

The Guardian offers an API as deep and robust as the New York Times Article API when it comes to content analysis.

The Guardian's API offers more than "1.7 million pieces of content", with published items as far back as 1999. You can register as a developer here, which gets you 5,000 API hits a day and an API key that looks something like this:

zzzyyyyy-9a9z-999z-z999-9e8a83922516

The Guardian has a handy interactive explorer to interactively tweak the query parameters.

@vasanthk
vasanthk / System Design.md
Last active November 25, 2025 15:26
System Design Cheatsheet

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

  1. Clarify and agree on the scope of the system
  • User cases (description of sequences of events that, taken together, lead to a system doing something useful)
    • Who is going to use it?
    • How are they going to use it?
@nickstanisha
nickstanisha / trie.py
Created November 21, 2015 22:58
An object-oriented implementation of a "Trie" in Python
class Node:
def __init__(self, label=None, data=None):
self.label = label
self.data = data
self.children = dict()
def addChild(self, key, data=None):
if not isinstance(key, Node):
self.children[key] = Node(key, data)
else:
@miloharper
miloharper / main.py
Created July 20, 2015 12:21
A simple neural network written in Python.
from numpy import exp, array, random, dot
class NeuralNetwork():
def __init__(self):
# Seed the random number generator, so it generates the same numbers
# every time the program runs.
random.seed(1)
# We model a single neuron, with 3 input connections and 1 output connection.