Bar Chart Race in Python with Matplotlib

~In roughly less than 50 lines of code

https://towardsdatascience.com/bar-chart-race-in-python-with-matplotlib-8e687a5c8a41

Java vs. Python: A Comparison of Features and Usage

Knowing when, not just how, to use a programming…

https://medium.com/better-programming/java-vs-python-a-comparison-of-features-and-usage-6f3629c723f4

Demystifying hypothesis testing with simple Python examples

Hypothesis testing is the bread and butter…

https://towardsdatascience.com/demystifying-hypothesis-testing-with-simple-python-examples-4997ad3c5294

pi-hole /



docker-pi-hole

Pi-hole in a docker container

https://github.com/pi-hole/docker-pi-hole

Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know

Sooner or later, every data science project faces an inevitable challenge: speed. Working with ...

https://blog.floydhub.com/multiprocessing-vs-threading-in-python-what-every-data-scientist-needs-to-know/

Beating the Dealer with Simple Statistics

Simulating Thousands of Blackjack Card Counting Strategies…

https://towardsdatascience.com/beating-the-dealer-with-simple-statistics-71b5e3701638

ShangtongZhang /



reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

https://github.com/ShangtongZhang/reinforcement-learning-an-introduction

Diving deeper into Python print

By Lenin Mishra
I write this blog with an intention of providing a more deeper context and ...

https://www.pylenin.com/blogs/python-print/

encode /



starlette

The little ASGI framework that shines. 🌟

https://github.com/encode/starlette

localstack /



localstack

💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline!

https://github.com/localstack/localstack

Understanding Python's asyncio

by Reuven M. Lerner

How to get ...

https://www.linuxjournal.com/content/understanding-pythons-asyncio

Python List Comprehension in 3 Minutes and 3 Reasons why you should use it

Let´s create our own animal…

https://towardsdatascience.com/python-list-comprehension-in-3-minutes-and-3-reasons-why-you-should-use-it-bf398654caf9

donnemartin /



data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

https://github.com/donnemartin/data-science-ipython-notebooks

Dealing with Categorical Data

Categorical data can screw up you ML model if not handled properly.

https://medium.com/machine-learning-eli5/dealing-with-categorical-data-f4c8556cbda0

Setting Up a Flask Application in Visual Studio Code

As a follow up to my Setting Up a Flask Application in PyCharm article, today I'm going to show you ...

http://blog.miguelgrinberg.com/post/setting-up-a-flask-application-in-visual-studio-code