Numerical-computing-is-fun - Learning numerical computing with notebooks for all ages.

Overview

As much as this series is to educate aspiring computer programmers and data scientists of all ages and all backgrounds, it is also a reminder to myself. After playing with computers and numbers for nearly 4 decades, I've also made this to keep in mind how to have fun with computers and maths.

Using Jupyter notebooks as an interactive learning medium, this series provides an introduction to:

  • Computer Science
  • Python programming language
  • Numerical computing
  • Numbers theory
  • Prime numbers
  • Data visualization
  • Deep learning

Interactive in Mybinder:

Binder

Interative in Azure (requires logging in):

Static in Nbviewer:

Use the link provided for each part below the corresponding title.

Launch in Binder (no login required)

Click the badge in the corresponding part below.

Part 1 : Introduction

Start learning here or

Binder

What you will learn:

  • print is the command to print something on the screen
  • Math operations are very easy to perform in Python
  • Python deals with numbers based on data types
  • In Python there are two numerical data types; int and float
  • Functions are powerful tools to easily perform various operations
  • Functions may accept arguments (parameters) as input
  • Functions are computer processes, and arguments are what is being processed
  • It's very easy to create your own functions

Part 2 : Prime Numbers

Continue learning here.

Binder

What you will learn:

  • Prime numbers relate with divisibility
  • Divisibility means that when one number is divided by other, the product is not a whole number
  • A prime number is any number that is divisible only by itself and 1
  • Binary means 0 and 1
  • Boolean logic is the binary language of computers
  • Python gives us an easy to use way to instruct computers
  • Boolean logic statements involve is, is not, and and or statements
  • Boolean statements can be joined together
  • Boolean statements always return either True or False as output
  • It's easy to perform computing operations with small numbers
  • The biggest prime number is a really big number
  • Very big numbers require vast networks of computers joined together

Part 3 : Algorithms Overview

Continue learning here.

Binder

What you will learn:

  • Algoritms are like insides of factories
  • Algoritms process inputs to produce outputs
  • Conditional statements are a tool for putting boolean logic in to action
  • Conditional statements are part of "flow control"
  • Flow controls give us the ability to create rules for computer programs
  • The three conditional statements in Python are if, else and elif
  • Even just if alone can be used to create a conditional statement

Part 4: Automation Overview

Continue learning here.

Binder

What you will learn:

  • Generally speaking computer programs are focused on process automation
  • Loops are a highly effective method for automation
  • With small changes to our code, we can make big improvements in capability
  • Sometimes we can get more done with less code!
  • It's very convinient to store values in to memory
  • Computer memory is nothing like human memory, and also not like a safe deposit box
  • Any value can be stored in to memory
  • Numbers can be automatically generated with range function
  • It's meaningful to learn new concepts by gradually improving things

CREDITS

Numerical Computing is Fun is an Eka Foundation project.

Owner
EKA foundation
EKA foundation
Set of models for classifcation of 3D volumes

Classification models 3D Zoo - Keras and TF.Keras This repository contains 3D variants of popular CNN models for classification like ResNets, DenseNet

69 Dec 28, 2022
Parasite: a tool allowing you to compress and decompress files, to reduce their size

🦠 Parasite 🦠 Parasite is a tool written in Python3 allowing you to "compress" any file, reducing its size. ⭐ Features ⭐ + Fast + Good optimization,

Billy 30 Nov 25, 2022
Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains

Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains This is an accompanying repository to the ICAIL 2021 pap

4 Dec 16, 2021
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination

Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l

DongYoung Kim 33 Jan 04, 2023
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

Multi-Agent-Deep-Deterministic-Policy-Gradients A Pytorch implementation of the multi agent deep deterministic policy gradients(MADDPG) algorithm This

Phil Tabor 159 Dec 28, 2022
Focal and Global Knowledge Distillation for Detectors

FGD Paper: Focal and Global Knowledge Distillation for Detectors Install MMDetection and MS COCO2017 Our codes are based on MMDetection. Please follow

Mesopotamia 261 Dec 23, 2022
[AAAI-2021] Visual Boundary Knowledge Translation for Foreground Segmentation

Trans-Net Code for (Visual Boundary Knowledge Translation for Foreground Segmentation, AAAI2021). [https://ojs.aaai.org/index.php/AAAI/article/view/16

ZJU-VIPA 2 Mar 04, 2022
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con

Tong Zekun 28 Jan 08, 2023
PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer.

Unsupervised_IEPGAN This is the PyTorch implementation of our ICCV 2021 paper Intrinsic-Extrinsic Preserved GANs for Unsupervised 3D Pose Transfer. Ha

25 Oct 26, 2022
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU

Xa9aX ツ 1.2k Dec 29, 2022
MAME is a multi-purpose emulation framework.

MAME's purpose is to preserve decades of software history. As electronic technology continues to rush forward, MAME prevents this important "vintage" software from being lost and forgotten.

Michael Murray 6 Oct 25, 2020
Simple-Image-Classification - Simple Image Classification Code (PyTorch)

Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima

Yechan Kim 8 Oct 29, 2022
Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Sionna: An Open-Source Library for Next-Generation Physical Layer Research Sionna™ is an open-source Python library for link-level simulations of digi

NVIDIA Research Projects 313 Dec 22, 2022
A PyTorch version of You Only Look at One-level Feature object detector

PyTorch_YOLOF A PyTorch version of You Only Look at One-level Feature object detector. The input image must be resized to have their shorter side bein

Jianhua Yang 25 Dec 30, 2022
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"

DRNet for Video Indvidual Counting (CVPR 2022) Introduction This is the official PyTorch implementation of paper: DR.VIC: Decomposition and Reasoning

tao han 35 Nov 22, 2022
Code accompanying the paper on "An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers" published at NeurIPS, 2021

Code for "An Empirical Investigation of Domian Generalization with Empirical Risk Minimizers" (NeurIPS 2021) Motivation and Introduction Domain Genera

Meta Research 15 Dec 27, 2022
Complete system for facial identity system

Complete system for facial identity system. Include one-shot model, database operation, features visualization, monitoring

4 May 02, 2022
Styled Augmented Translation

SAT Style Augmented Translation Introduction By collecting high-quality data, we were able to train a model that outperforms Google Translate on 6 dif

139 Dec 29, 2022
PyTorch-centric library for evaluating and enhancing the robustness of AI technologies

Responsible AI Toolbox A library that provides high-quality, PyTorch-centric tools for evaluating and enhancing both the robustness and the explainabi

24 Dec 22, 2022
UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems

[ICLR 2021] "UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems" by Jiayi Shen, Haotao Wang*, Shupeng Gui*, Jianchao Tan, Zhangyang Wang, and Ji Liu

VITA 39 Dec 03, 2022