Do you use PyCharm as your Python IDE?. Then this course might be of interest to you. Taught by Michael of TalkPython podcast fame.
I love VS Code and I love Jupyter Notebooks. Both excel at their own world. But to improve my workflow I had to create a bridge between their worlds.
GoCD is a continuous delivery tool supporting modern infrastructure with elastic on-demand agents and cloud deployments. With GoCD, you can easily model, orchestrate and visualize complex workflows from end to end. It’s open source, free to use and download.
The O’Reilly Programming Podcast: A look at some of Python’s valuable, but often overlooked, features.
It provides a management GUI, a slew of scientifically oriented work environments, and tools to simplify the process of using Python for data crunching
Ensembles have rapidly become one of the hottest and most popular methods in applied machine learning. Virtually every winning Kaggle solution features them, and many data science pipelines have ensembles in them.
Put simply, ensembles combine predictions from different models to generate a final prediction, and the more models we include the better it performs. Better still, because ensembles combine baseline predictions, they perform at least as well as the best baseline model. Ensembles give us a performance boost almost for free!
Embed docs directly on your website with a few lines of code. Test the API for free.
We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the “analyse skeletons” plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python.
K-means clustering is a simple yet very effective unsupervised machine learning algorithm for data clustering. It clusters data based on the Euclidean distance between data points. K-means clustering algorithm has many uses for grouping text documents, images, videos, and much more.
This is an early developer preview of Python 3.7
Renko charts are time independent and are efficient to trade as they eliminate noise. In this article we see how to plot renko charts of any instrument with OHLC data using Python.
This tutorial will walk through using Google Cloud Speech API to transcribe a large audio file.
Essential codes for jump-starting machine learning/data science with Python.
Additive models for time series modeling
When it comes to natural language generation, people normally think of advanced AI systems using advanced mathematics; however, that is not always true. In this post, I will be using the idea of Markov chains and a small dataset of quotes to generate new quotes.
In this lesson, you will be introduced to Python generators. You will see how a generator can replace a common function and learn the benefits of doing so. You will learn what role the yield keyword provides in functions and how it differs from a return. Building on that knowledge, you will learn how to build a generator to recursively crawl an API (swapi.co) and return Star Wars characters from "The Force Awakens".
When no one will follow you, you can do it yourself.
A library for manipulating Pipenv projects.
Paste in some broken unicode text and FTFY will tell you how to fix it!
A python script for smart lightbulbs to indicate how badly you're losing money
Use word vectors to interactively generate lists of similar words
A Sublime plugin for Pipenv.
The pretrained models trained on Moments in Time Dataset
PyOrphan show suggestion of unused code in your python project.
Runtime type inference for Python
Ensure all of your repositories are watched.