A common problem people often run up against in Python is understanding a method to sort one list based on the values in another. There are many solutions to this but I will select three main methods, one of which uses well-understood Python built-in functions such as zip() and sorted(). One will use the dictionary … Read more
This article is a collection of useful machine learning cheat sheets focusing on the Python libraries such as Theano, Keras, TensorFlow, PyTorch, NetworkX, and other ML-related Python libraries. You may want to check out these great resources that cover many of these topics at once: https://becominghuman.ai/cheat-sheets-for-ai-neural-networks-machine-learning-deep-learning-big-data-science-pdf-f22dc900d2d7 https://gto76.github.io/python-cheatsheet/ https://www.pythonsheets.com/ Theano Cheat Sheets Theano is a Library … Read more
Hey Finxters! Have you ever felt surrounded by developers boasting from their latest app in prod hosted in the cloud? Or the need for making yours too but overwhelmed by the technicalities involved? Needed to set up quickly and easily a mini data science demo website without resorting to web developers? Or simply wanting to … Read more
Python’s S.symmetric_difference(T) method creates and returns a new set containing all elements that are in exactly one of the two sets S and T. Here’s a minimal example where we return a new set containing the elements 1 and 4 that are in exactly one of the two sets s and t. Here’s another visual … Read more
Quick Answer: Static attributes are variables defined once for the class and shared by all instances. Dynamic attributes are variables defined for individual instances only. Static variables are used as a “fall-back” when there are no explicit dynamic attributes defined for the instances. When you try to “overwrite” a static attribute such as in x.attr … Read more
? This tutorial will show you the most simple and straightforward way to implement linear regression in Python—by using scikit-learn’s linear regression functionality. I have written this tutorial as part of my book Python One-Liners where I present how expert coders accomplish a lot in a little bit of code. Feel free to bookmark and download … Read more
Are you confronted with a JSON file and at a loss to know how to extract wanted information, or you don’t know about JSON but would like to? Today we’ll introduce the JSON format and use Python to access a JSON file. We’ll extract the data we need and we’ll use the Python JSON module … Read more
Summary: This blog explains the ways to apply a given function to each element of a list. The best way to apply a function to each element of a list is to use the Python built-in map() function that takes a function and one or more iterables as arguments. It then applies the function to … Read more
Python’s set.remove(x) method removes an element x from this set if it is a member, otherwise it raises a KeyError. Here’s a minimal example where you remove the string element ‘Bob’ from the set by means of the s.remove() method: Syntax Let’s dive into the formal syntax of the set.remove() method. set.remove(element) Argument Data Type … Read more
In this article you will learn:
How To Check if One String is a Subsequence of Another?
This article gives you everything you need to know about sets in Python. To make it a bit more fun, I have used Harry Potter examples throughout the article. What is a Python Set? The set data structure is one of the basic collection data types in Python and many other programming languages. In fact, … Read more
NumPy’s np.diff() function calculates the difference between subsequent values in a NumPy array. For example, np.diff([1, 2, 4]) returns the difference array [1 2]. Here is a simple example to calculate the Fibonacci number differences: This code snippet shows the most simple form of the np.diff() method: how to use it on a one-dimensional NumPy … Read more