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Introduction to Bayesian Modeling with PyMC3 - Dr. Juan Camilo Orduz
This post is devoted to give an introduction to Bayesian modeling using PyMC3, an open source probabilistic programming framework written in Python.
Python  Bayesian  PyMC3  tutorial  probability  statistics  math 
9 days ago by areich
How to Build a Blockchain in Python (Get Pre-built Runtime) | ActiveState
The system that Bitcoin relies upon — a growing list of records (i.e. blocks) that are linked to one another — is known as a blockchain. Bitcoin was the first successful application of this system, and shortly after its rise in popularity, other cryptocurrencies were founded on the same principles. This system, however, is not restricted to storing financial information. Rather, the type of data being stored is inconsequential to and independent of the blockchain network. 
Python  blockchain  bitcoin  tutorial 
6 weeks ago by areich
Building a Python C Extension Module – Real Python
Learn how to write Python interfaces in C. Find out how to invoke C functions from within Python and build Python C extension modules. You’ll learn how to parse arguments, return values, and raise custom exceptions using the Python API.
Python  C  extension  module  tutorial 
october 2019 by areich
A Gentle Introduction to Lattices and Lattice-Based Key Exchange: Part 1
This post gives a (hopefully!) simple introduction to lattices and hard problems based on lattices. Lattices are interesting to the field of cryptography as the below problems are difficult for a quantum computer to solve, as opposed to problems based on discrete logarithms or factoring such as Diffie-Hellman based problems or RSA.
cryptography  lattices  tutorial  key  exchange 
june 2019 by areich
Regression with Probabilistic Layers in TensorFlow Probability
Here, we demonstrate in more detail how to use TFP layers to manage the uncertainty inherent in regression predictions.
TensorFlow  probability  gaussianprocess  regression  tutorial  Python  machinelearning 
march 2019 by areich
How to Distribute a wxPython Application | The Mouse Vs. The Python
what you will learn here is how to turn your application into an executable
wxpython  tutorial  Python  GUI  distribution  executable 
march 2019 by areich
How to Build a Python GUI Application With wxPython – Real Python
In this article, you’ll learn how to build a graphical user interface with Python using the wxPython GUI toolkit.
wxpython  tutorial  Python  GUI 
march 2019 by areich
Machine Learning for Beginners: An Introduction to Neural Networks -
A simple explanation of how they work and how to implement one from scratch in Python.
machinelearning  neuralnetworks  tutorial  Python  blog 
march 2019 by areich
Generating Random Data in Python (Guide) – Real Python
Here, you’ll cover a handful of different options for generating random data in Python, and then build up to a comparison of each in terms of its level of security, versatility, purpose, and speed.
cryptography  Python  random  number  RNG  generator  tutorial 
january 2019 by areich
Jupyter Notebooks Advanced Tutorial
Following on from "Jupyter Notebook for Beginners: A Tutorial", this guide will take you on a journey from the truly vanilla to the downright dangerous. That's right! Jupyter's wacky world of out-of-order execution has the power to faze, and when it comes to running notebooks inside notebooks, things can get complicated fast.
Python  Jupyter  notebook  tutorial  advanced  blog 
january 2019 by areich
Alone Djangonaut – A tour on Python Packaging
If you're new to Python or a mature one and want to share your code with other developers or you have build a library to be used by end users and you're struggle with the packaging, then this tutorial/post/explanatory guide is (possibly) for you.
package  Python  library  tutorial 
november 2018 by areich
MCMC sampling for dummies
This blog post is an attempt at trying to explain the intuition behind MCMC sampling (specifically, the random-walk Metropolis algorithm). Critically, we'll be using code examples rather than formulas or math-speak. Eventually you'll need that but I personally think it's better to start with the an example and build the intuition before you move on to the math.
statistics  Bayesian  MCMC  tutorial  datascience  Python  sampling 
november 2018 by areich
Jupyter Notebook Viewer
This notebook was derived from the Caltech "Learning from Data" course, specifically Lecture 9 on the logistic regression model. It is a simple Python implementation of the logistic regression model using NumPy.
Python  Jupyter  notebook  logistic  regression  NumPy  tutorial 
november 2018 by areich
Make a PEX from Python script | Peter Demin
Python is a great language for scripting. But there is a problem with distributing working executable. If script uses any non built-in dependency, it can’t be just copied to the target host and executed.

One possible solution is using PEX - Python EXecutable. It packs the script with dependencies inside a single binary.
Python  executable  PEX  tutorial  script 
november 2018 by areich
Essential Watercolor Techniques: Composition with Gordon MacKenzie
In this video demonstration, Gordon MacKenzie shares his painting techniques for using composition to enhance the impact of your work. Discover watercolor techniques for wet-into-wet painting, lifting, glazing, and more as you create two watercolor paintings from start to finish
art  tutorial  watercolor  painting  MacKenzie  video 
october 2018 by areich
What is Public Key Cryptography? - Twilio
This post will dive into modern cryptography, an overview of how it works, and its everyday use cases — including how Twilio uses public-key crypto in our Authy application and to secure our API.
Python  tutorial  cryptography  public-key  Twilio  Authy 
september 2018 by areich
PyQt5 tutorial: Create a Python GUI in 2018
This tutorial shows how you can use PyQt5 to build a desktop app with Python. It covers everything from the best way to set up PyQt in 2018, to compiling your app and distributing it to other people's computers. You can use Windows, Mac or Linux. The only prerequisite is that you have Python 3 (ideally 3.5) installed.
Python  GUI  tutorial  PyQt5  UI 
september 2018 by areich
Introduction to Bayesian modeling with PyMC3 | Dr. Juan Camilo Orduz
This post is devoted to give an introduction to Bayesian modeling using PyMC3, an open source probabilistic programming framework written in Python. Part of this material was presented in the Python Users Berlin (PUB) meet up.
Python  Bayesian  modeling  PyMC3  tutorial  MCMC  MarkovChains  Metropolis-Hastings  Coursera 
september 2018 by areich
One Point Perspective Drawing: The Ultimate Guide
This article contains everything an Art student needs to know about drawing in one point perspective. It includes step-by-step tutorials, lesson plans, handouts, videos and free downloadable worksheets. The material is suitable for middle and high school students, as well as any other person who wishes to learn how to draw using single point perspective. It is written for those with no prior experience with perspective, beginning with basic concepts, before working towards more complex three-dimensional forms.
art  drawing  perspective  tutorial  one-point 
august 2018 by areich
Python Histogram Plotting: NumPy, Matplotlib, Pandas & Seaborn – Real Python
In this tutorial, you’ll be equipped to make production-quality, presentation-ready Python histogram plots with a range of choices and features.
Python  matplotlib  seaborn  histograms  plotting  numpy  pandas  tutorial 
july 2018 by areich
Programming in Scala, First Edition
Programming in Scala, First Edition
by Martin Odersky, Lex Spoon, and Bill Venners
December 10, 2008
Scala  tutorial  book  programming  functional 
july 2018 by areich
A Simple Tutorial on How to document your Python Project using Sphinx and Rinohtype
In this tutorial, I’ll be using Sphinx and Rinohtype to produce an HTML and PDF documentation files respectively to a simple API project I wrote that manages a list of Teacher records (Github Project Link) .
Python  documentation  Sphinx  Rinohtype  tutorial 
june 2018 by areich
Easy TensorFlow - Home
Learn Tensorflow like shelling peas!
Our mission is to help you master programming in Tensorflow
step by step, with simple tutorials, and from A to Z
tutorial  machinelearning  deeplearning  neuralnetworks  tensorflow 
may 2018 by areich
Part-of-Speech tagging tutorial with the Keras Deep Learning library
In this tutorial, you will see how you can use a simple Keras model to train and evaluate an artificial neural network for multi-class classification problems.
Python  NLTK  NLP  part-of-speech  POS  Keras  deeplearning  neuralnetwork  tutorial  blog 
april 2018 by areich
Crypto 101
Crypto 101 is an introductory course on cryptography, freely available for programmers of all ages and skill levels.
cryptography  books  course  online  tutorial  Crypto101 
april 2018 by areich
Python 3: An Intro to Encryption | The Mouse Vs. The Python
Python 3 doesn’t have very much in its standard library that deals with encryption. Instead, you get hashing libraries. We’ll take a brief look at those in the chapter, but the primary focus will be on the following 3rd party packages: PyCrypto and cryptography. We will learn how to encrypt and decrypt strings with both of these libraries.
cryptography  encryption  Python  tutorial  PyCrypto  hashing 
april 2018 by areich
Tutorial: What is WordNet? A Conceptual Introduction Using Python |
This tutorial is a gentle introduction to WordNet concepts, using TextBlob for the examples. To follow along with the examples, make sure you have the latest version of TextBlob.
Python  tutorial  WordNet  TextBlob  NLTK  NLP  blog 
february 2018 by areich
Build a Neural Network with Python
Neural networks can be intimidating, especially for people new to machine learning. However, this tutorial will break down how exactly a neural network works and you will have a working flexible neural network by the end. Let’s get started!
neuralnetworks  deeplearning  machinelearning  Python  tutorial 
february 2018 by areich
A friendly Introduction to Backpropagation in Python | Sushant Choudhary
My aim here is to test my understanding of Karpathy’s great blog post “Hacker’s guide to Neural Networks” as well as of Python, to get a hang of which I recently perused through Derek Banas’ awesome commented code expositions. As someone steeped in R and classical statistical learning methods for structured data, I’m very new to both Python as well as Neural nets, so it is best not to fall into the easy delusions of competence that stem from being able to follow things while reading about them. Therefore, code.
tutorial  machinelearning  blog  neuralnetwork  Python 
december 2017 by areich
Ahmed BESBES - Data Science Portfolio – Understanding deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras
In this article, I'll go beyond the overall hype you'd encounter in the mass media and present a concrete application of deep learning.

I'll show you how to build a deep neural network that classifies images to their categories with an accuracy of a 90%. This seemingly simple task is a very hard problem that computer scientists have been working on for years before the rose of deep networks and especially Convolutional Neural Networks (CNN).
tutorial  deeplearning  neuralnetworks  CNN  ImageProcessing  AWS  Kera  TensorFlow  Blog 
november 2017 by areich
TensorFlow Neural Network Tutorial
TensorFlow applications can be written in a few languages: Python, Go, Java and C. This post is concerned about its Python version, and looks at the library's installation, basic low-level components, and building a feed-forward neural network from scratch to perform learning on a real dataset.
TensorFlow  neuralnetworks  tutorial  blog  Python 
november 2017 by areich
How to Use t-SNE Effectively
Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively.
machinelearning  visualization  t-SNE  dimensionreduction  blog  tutorial 
november 2017 by areich
Build Your Own Blockchain Part 1 — Creating, Storing, Syncing, Displaying, Mining, and Proving Work | Big-Ish Data
In this post, I’ll show the way I want to store the blockchain data and generate an initial block, how a node can sync up with the local blockchain data, how to display the blockchain (which will be used in the future to sync with other nodes), and then how to go through and mine and create valid new blocks. For this first post, there are no other nodes. There are no wallets, no peers, no important data. Information on those will come later.
tutorial  blockchain  bitcoin  Python 
october 2017 by areich
The Python Dictionary—The Sharat's
The Python Dictionary is a key–value style data structure that is tightly integrated with the language syntax and semantics. Understanding them well can help us use them better and investigate subtle problems more efficiently.

This is my attempt to document this topic in more depth. Though I included a small section about the syntax and basic usage of dictionaries, it’ll be helpful if you have some beginner–intermediate level experience with Python.

This article is written for Python 3.6 installed via Anaconda on Xubuntu.
Python  dictionary  tutorial  blog  key-value 
october 2017 by areich
How to Generate FiveThirtyEight Graphs in Python
Using Python’s matplotlib and pandas, we’ll see that it’s rather easy to replicate the core parts of any FiveThirtyEight (FTE) visualization.
Python  visualization  FiveThirtyEight  FTE  matplotlib  pandas  graphs  tutorial  blog 
october 2017 by areich
A guide to logging in Python |
This article looks at Python's logging module, its design, and ways to adapt it for more complex use cases.
Python  logging  tutorial  blog 
october 2017 by areich
NLP Tutorial Using Python NLTK (Simple Examples) - Like Geeks
In this post, we will talk about natural language processing (NLP) using Python. This NLP tutorial will use Python NLTK library. NLTK is a popular Python library which is used for NLP.
NLP  NLTK  Python  tutorial  blog 
october 2017 by areich
Bloom Filters for the Perplexed
An introduction to standard Bloom filters
A python based toy implementation
Example: Efficiently Verify Compromised SSH Keys

Breaking Bitcoin (and Ethereum) Brainwallets
Search Engine Optimizations
Recommender Systems Optimization

A derivation of the underlying math for the rusty-engineer
Bloomfilter  tutorial  blog  SSH  recommender  SEO  bitcoin  ethereum  brainwallets 
october 2017 by areich
Learn Blockchains by Building One – Hacker Noon
The fastest way to learn how Blockchains work is to build one
blockchain  tutorial  Python 
october 2017 by areich
Understanding datetime in Python: A primer |
Get a better understanding of datetime in Python with this primer.
dates  bestpractices  datetime  time  Python  tutorial  blog 
september 2017 by areich
Bagging / Bootstrap Aggregation with R
Practical walkthroughs on machine learning, data exploration and finding insight.
bagging  bootstrap  aggregation  machinelearning  tutorial  blog  R 
september 2017 by areich
Understanding Python's logging module | weblog
In this article I want to bring attention to some of the misconceptions I had about the logging module. I'm going to assume you have a basic understanding of how it works and know about loggers, log levels and handlers.
Python  logging  tutorial  blog  loggers  handlers 
august 2017 by areich
The Magic Behind Python Generator Functions – Syed Komail Abbas – Medium
Generator Functions are one of the coolest features of the Python programming language. There are numerous articles on the web describing the many benefits generator functions provide in terms of speed, scalability and memory efficiency of our python programs. However, there is not much material out there which sheds light on how generator functions actually work behind the scenes. This article attempts to fill this void by shedding light on some of the key features of the python programming language which make generator functions possible.
Python  generators  yield  tutorial  blog 
august 2017 by areich
An end to end implementation of a Machine Learning pipeline
deeplearning  tutorial  machinelearning 
august 2017 by areich
Deploy Your Python Functions as a REST API
This tutorial demonstrates how to deploy an arbitrary python function as an api with Bluemix and Flask -- complete with clean, intuitive Swagger API documentation.
Python  IBM  Bluemix  Flask  REST  API  tutorial 
july 2017 by areich
Let’s Create Our Own Cryptocurrency |
This implementation will not include smart contracts, transaction rewards, nor utilize Merkel trees. Its only purpose is to act as a decentralized ledger. It is rudimentary, but I will eventually fork a few experimental blockchains with advanced features from this one.
blockchain  cryptocurrency  blog  tutorial  Python 
july 2017 by areich
A peek under Bitcoin's hood | Sam Lewis
This post walks through the process of creating a minimally viable Bitcoin client that can create a transaction and submit it to the Bitcoin peer to peer network so that it is included in the Blockchain.
Python  bitcoin  blockchain  tutorial  Blog 
june 2017 by areich
Blockchain Demo
Brief video demo of blockchain
video  bitcoin  blockchain  hash  sha256  demo  tutorial 
june 2017 by areich
The Hitchhiker’s Guide to Python! — The Hitchhiker's Guide to Python
This handcrafted guide exists to provide both novice and expert Python developers a best practice handbook to the installation, configuration, and usage of Python on a daily basis.
Python  bestpractices  handbook  hitchhiker  guide  tutorial  reference 
may 2017 by areich
Explain like I’m 5: Kerberos – roguelynn
While this topic probably can not be explained to a 5 year-old and be understood, this is my attempt at defragmenting documentation with some visual aids and digestible language.
kerberos  authentication  cyber  tutorial  blog 
may 2017 by areich
Learning Deep Learning with Keras
Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over3, this post is for you! Its goal is not to teach neural networks by itself, but to provide an overview and to point to didactically useful resources.
deeplearning  neuralnetworks  resources  blog  tutorial 
may 2017 by areich
A Beginner's Guide to Neural Networks in Python and SciKit Learn 0.18 - Springboard Blog
The most popular machine learning library for Python is SciKit Learn. The latest version (0.18) now has built in support for Neural Network models! In this article we will learn how Neural Networks work and how to implement them with the Python programming language and the latest version of SciKit-Learn! Basic understanding of Python is necessary to understand this article, and it would also be helpful (but not necessary) to have some experience with Sci-Kit Learn.
Python  SciKit-Learn  neuralnetwork  tutorial  blog 
may 2017 by areich
On Recursion, Continuations and Trampolines - Eli Bendersky's website
How is tail recursion different from regular recursion? What do continuations have to do with this, what is CPS, and how do trampolines help? This article provides an introduction, with code samples in Python and Clojure.
Python  Clojure  recursion  closure  continuation  CPS  trampoline  tutorial  blog 
april 2017 by areich
Python Decorators: A Step-By-Step Introduction –
Understanding decorators is a milestone for any serious Python programmer. Here’s your step-by-step guide to how decorators can help you become a more efficient and productive Python developer.
Python  tutorial  blog  decorators 
april 2017 by areich
TensorFlow RNN Tutorial: Building, Training, and Improving on Existing Recurrent Neural Networks - Silicon Valley Data Science
On the deep learning R&D team at SVDS, we have investigated Recurrent Neural Networks (RNN) for exploring time series and developing speech recognition capabilities. Many products today rely on deep neural networks that implement recurrent layers, including products made by companies like Google, Baidu, and Amazon.
deeplearning  neuralnetworks  recurrent  RNN  timeseries  audio  speech  recognition  tutorial  blog 
march 2017 by areich
Analyzing 4 Million Yelp Reviews with Python on AWS | DevelopIntelligence Blog
Yelp runs a data challenge every year in which it invites people to explore its real-world datasets for unique insights. In this post, we’ll cover show how to load the dataset into a Jupyter Notebook running on a powerful but cheap AWS spot instance, and produce some initial explorations and visualizations.
Python  AWS  tutorial  Jupyter  Notebook  Yelp  data  analytics  visualization  blog 
march 2017 by areich
A Guide to Deep Learning by YerevaNN
Deep learning is a fast-changing field at the intersection of computer science and mathematics. It is a relatively new branch of a wider field called machine learning. The goal of machine learning is to teach computers to perform various tasks based on the given data. This guide is for those who know some math, know some programming language and now want to dive deep into deep learning.
tutorial  machinelearning  deeplearning  neuralnetworks  CNN  RNN  autoencoders  graphicalmodels  guide 
january 2017 by areich
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