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Issue - 148

Worthy Read

This video series covers the history of CD, concepts, best practices, how to get started, and popular tools. You'll gain a holistic view of continuous delivery and a deeper understanding and appreciation of critical concepts.

A Step by Step Guide with Code Snippets for Packing Your Python 2.7 Function for AWS Lambda.
aws lambda

Over the past year, I’ve spent most of my working time doing deep learning research and internships. And a lot of that year was making very big mistakes that helped me learn a lot about not just about ML, but about how to engineer these systems correctly and soundly. One of the main principles I learned during my time at Google Brain was that unit tests can make or break your algorithm and can save you weeks of debugging and training time.
machine learning

Zulip is the world’s most productive team chat software, an alternative to Slack, HipChat, and IRC. Zulip combines the immediacy of chat with the asynchronous efficiency of email, and is 100% free and open source software.
new release

This post is an attempt to we better understand the Tree Data Structure and clarify any doubts about it. We will learn about what is a tree, examples of it, its terminology, how it works, and a technical implementation (a.k.a code!)
data structure

Test the API for free.

Do you really know how you ended up with those results after analyzing the data from Public Source?

Catch Errors Before Users Do.

Note - If you have read Writing Idiomatic Python - By Jeff Knupp. You might want to read what Oleksandr has to say in this post. Personally I learned a lot from the book and recommend it regularly to everyone. People don’t speak entirely in idioms unless they are totally off their rockers. Overusing idioms makes you seem more than self-confident, full of air, and frankly not playing with a full deck. It is fair to middling to spice your language with idioms a little bit, but build the whole speech entirely out of them is beside the point.

TensorFlow is an open source machine learning library developed at Google. TensorFlow uses data flow graphs for numerical computations. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. In this post we will learn very basics of TensorFlow and we will build a Logistic Regression model using TensorFlow.

We are extremely pleased to announce the release of SciPy 1.0, 16 years after version 0.1 saw the light of day. It has been a long, productive journey to get here, and we anticipate many more exciting new features and releases in the future.
new release

This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.

Dramatiq is a distributed task processing library for Python with a focus on simplicity, reliability and performance.

Welcome to "Bayesian Modelling in Python" - a tutorial for those interested in learning how to apply bayesian modelling techniques in python (PYMC3). This tutorial doesn't aim to be a bayesian statistics tutorial - but rather a programming cookbook for those who understand the fundamental of bayesian statistics and want to learn how to build bayesian models using python. The tutorial sections and topics can be seen below.

In my talk at Clojure Conj I mentioned how a project from Oracle Labs named GraalVM might have to potential for Clojure to interop with Python on the same VM. At the time of the talk, I had just learned about it so I didn’t have time to take a look at it. Over the last week, I’ve managed to take it for a test drive and I wanted to share what I found.

Through my career as a software developer, I have appreciated one text editor the most, Sublime Text. I began with writing code in Notepad++ long long time ago, then tried IDEs as well but nothing came as close to working smoothly as Sublime Text. This blog is also written using Sublime Text.

Why are we offering cloud Jupyter notebooks? If you use Jupyter or IPython notebooks for your business or for working on assignments or research work, you are probably familiar with the challenges that come with setting up a stable Jupyter system on a machine.

code snippets

Exercises for k-means clustering with Python 3 and scikit-learn as Jupyter Notebooks, with full solutions provided as notebooks and as PDFs. These exercises teach the fundamentals of k-means using some great real-world datasets, including stock price movements, measurements of fish and seed dimensions.

Slit-scan photography is a technique where a slit is moved between the camera and the subject. It’s effect lets the viewer see a tiny slice of a movement, through time.
image processing

I was once a huge fan of FSMs (Finite State Machines) as a mechanism to keep track of states. Automata theory is the basis of class of computational problems solvable by discrete math. I had used fysom in the past but this time I wanted something home grown. I was able to write complex language parse in a couple hours using only 200 lines of code.



babybuddy - 422 Stars, 14 Fork
A buddy for :baby: Helps caregivers track sleep, feedings, diaper changes, and tummy time to learn about and predict baby's needs without (as much) guess work.

progressive_growing_of_gans - 411 Stars, 36 Fork
Progressive Growing of GANs for Improved Quality, Stability, and Variation

flask-webpack-cookiecutter - 42 Stars, 2 Fork
Auto builds the foundation for a production ready Flask+Webpack application

deepvoice3 - 35 Stars, 5 Fork
Tensorflow Implementation of Deep Voice 3.

hacktoberfest-projecteuler - 21 Stars, 147 Fork
This repo contains solutions for projecteuler problems in multiple languages. Specially created for newcomers to contribute as part of Hacktoberfest Challenge.

skip-gram-pytorch - 17 Stars, 0 Fork
A complete pytorch implementation of skip-gram. - 9 Stars, 0 Fork
Python Wrapper around the CircleCI API.

Pyava - 6 Stars, 0 Fork
A simple emulator launcher written in Python.

Alexa-wisdomQuotes - 1 Stars, 0 Fork
Enabling Alexa to get quotes from