python_tutorials
Python

Seaborn Box Plot – Tutorial and Examples

Introduction Seaborn is one of the most widely used data visualization libraries in Python, as an extension to Matplotlib. It offers a simple, intuitive, yet highly customizable API for data visualization. In this tutorial, we’ll take a look at how to plot a Box Plot in Seaborn. Box plots are used to visualize summary statistics of a dataset, displaying attributes of the distribution like the data’s range and distribution. Import Data We’ll need to select a dataset with continuous features […]

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python_tutorials
Python

Integrating MongoDB with Flask Using Flask-PyMongo

Introduction Building a web app almost always means dealing with data from a database. There are various databases to choose from, depending on your preference. In this article, we shall be taking a look at how to integrate one of the most popular NoSQL databases – MongoDB – with the Flask micro-framework. They are several Flask extensions for integrating MongoDB, here we’ll be using the Flask-PyMongo extension. We will also be working on a simple Todo-List API to explore the […]

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python_tutorials
Python

Matplotlib Box Plot – Tutorial and Examples

Introduction There are many data visualization libraries in Python, yet Matplotlib is the most popular library out of all of them. Matplotlib’s popularity is due to its reliability and utility – it’s able to create both simple and complex plots with little code. You can also customize the plots in a variety of ways. In this tutorial, we’ll cover how to plot Box Plots in Matplotlib. Box plots are used to visualize summary statistics of a dataset, displaying attributes of […]

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Programming languages and software engineering Leave a comment

LAMBDA: The ultimate Excel worksheet function

Ever since it was released in the 1980s, Microsoft Excel has changed how people organize, analyze, and visualize their data, providing a basis for decision-making for the millions of people who use it each day. It’s also the world’s most widely used programming language. Excel formulas are written by an order of magnitude more users than all the C, C++, C#, Java, and Python programmers in the world combined. Despite its success, considered as a programming language Excel has fundamental […]

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Machine Learning

How to Use Nelder-Mead Optimization in Python

The Nelder-Mead optimization algorithm is a widely used approach for non-differentiable objective functions. As such, it is generally referred to as a pattern search algorithm and is used as a local or global search procedure, challenging nonlinear and potentially noisy and multimodal function optimization problems. In this tutorial, you will discover the Nelder-Mead optimization algorithm. After completing this tutorial, you will know: The Nelder-Mead optimization algorithm is a type of pattern search that does not use function gradients. How to […]

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Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 66: Means against ends of sentences

This week I am going to revisit the mystery of decoding in neural machine translation for one more time. It has been more than a year ago when Felix Stahlberg and Bill Byrne discovered the very disturbing feature of neural machine translation models – that the most probable target sentence is an empty sequence and this it is a sort of luck that we decode good translations from the models (MT Weekly 20). The paper disproved the narrative of NMT […]

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python_tutorials
Python

How to Iterate Over a Dictionary in Python

Introduction Dictionaries are one of the most used data structures in all of software development, and for a good reason. They allow us to store our data in neat key, value pairs, which in turn gives us the ability to, on average, access our data in O(1) time. While using a dictionary it’s important to know how to iterate over it. Not being able to recover the data you stored makes it practically useless. In this article, we’ll see how […]

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Machine Learning

Regression Metrics for Machine Learning

Regression refers to predictive modeling problems that involve predicting a numeric value. It is different from classification that involves predicting a class label. Unlike classification, you cannot use classification accuracy to evaluate the predictions made by a regression model. Instead, you must use error metrics specifically designed for evaluating predictions made on regression problems. In this tutorial, you will discover how to calculate error metrics for regression predictive modeling projects. After completing this tutorial, you will know: Regression predictive modeling […]

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Machine Learning

How to Get Started With Recommender Systems

Recommender systems may be the most common type of predictive model that the average person may encounter. They provide the basis for recommendations on services such as Amazon, Spotify, and Youtube. Recommender systems are a huge daunting topic if you’re just getting started. There is a myriad of data preparation techniques, algorithms, and model evaluation methods. Not all of the techniques will be relevant, and in fact, the state-of-the-art can be ignored for now as you will likely get very […]

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