October 28, 2020 Artificial intelligence Leave a comment

Enabling interaction between mixed reality and robots via cloud-based localization

You are here. We see some representation of this every day—a red pin, a pulsating blue dot, a small graphic of an airplane. Without a point of reference on which to anchor it, though, here doesn’t help us make our next move or coordinate with others. But in the context of an office building, street, or U.S. map, “here” becomes a location that we can understand in relation to other points. We’re near the lobby; at the intersection of Broadway […]

October 28, 2020 Machine Learning

Error-Correcting Output Codes (ECOC) for Machine Learning

Machine learning algorithms, like logistic regression and support vector machines, are designed for two-class (binary) classification problems. As such, these algorithms must either be modified for multi-class (more than two) classification problems or not used at all. The Error-Correcting Output Codes method is a technique that allows a multi-class classification problem to be reframed as multiple binary classification problems, allowing the use of native binary classification models to be used directly. Unlike one-vs-rest and one-vs-one methods that offer a similar […]

Machine Translation Weekly 56: Beam Search and Models’ Surprisal

Last year an EMNLP paper “On NMT Search Errors and Model Errors: Cat Got Your Tongue?” (that I discussed in MT Weekly 20) showed a mindblowing property of neural machine translation models that the most probable target sentence is not necessarily the best target sentence. In NMT, we model the target sentence probably that is factorized using the chain rule into conditional token probabilities. We can imagine the target sentence generation like this: The model estimates the probability of the […]

October 26, 2020 Machine Learning

Why Use Ensemble Learning?

What are the Benefits of Ensemble Methods for Machine Learning? Ensembles are predictive models that combine predictions from two or more other models. Ensemble learning methods are popular and the go-to technique when the best performance on a predictive modeling project is the most important outcome. Nevertheless, they are not always the most appropriate technique to use and beginners the field of applied machine learning have the expectation that ensembles or a specific ensemble method are always the best method […]

October 25, 2020 Python

Sentiment Analysis in Python With TextBlob

Introduction State-of-the-art technologies in NLP allow us to analyze natural languages on different layers: from simple segmentation of textual information to more sophisticated methods of sentiment categorizations. However, it does not inevitably mean that you should be highly advanced in programming to implement high-level tasks such as sentiment analysis in Python. Sentiment Analysis The algorithms of sentiment analysis mostly focus on defining opinions, attitudes, and even emoticons in a corpus of texts. The range of established sentiments significantly varies from […]

October 24, 2020 Machine Learning

A Gentle Introduction to Ensemble Learning

Many decisions we make in life are based on the opinions of multiple other people. This includes choosing a book to read based on reviews, choosing a course of action based on the advice of multiple medical doctors, and determining guilt. Often, decision making by a group of individuals results in a better outcome than a decision made by any one member of the group. This is generally referred to as the wisdom of the crowd. We can achieve a […]

October 22, 2020 Python

Python: Check Index of an Item in a List

Introduction Lists are useful in different ways compared to other datatypes because of how versatile they are. In this article we’ll take a look at one of the most common operations with lists – finding the index of an element. We will take a look at different scenarios of finding an element, i.e. finding the first, last, and all occurrences of an element. As well as what happens when the element we’re looking for doesn’t exist. Using the index() Function […]

October 22, 2020 Python

How to Iterate over Rows in a Pandas DataFrame

Introduction Pandas is an immensely popular data manipulation framework for Python. In a lot of cases, you might want to iterate over data – either to print it out, or perform some operations on it. In this tutorial, we’ll take a look at how to iterate over rows in a Pandas DataFrame. If you’re new to Pandas, you can read our beginner’s tutorial. Once you’re familiar, let’s look at the three main ways to iterate over DataFrame: items() iterrows() itertuples() […]

October 22, 2020 Python

Matplotlib Scatter Plot – Tutorial and Examples

Introduction Matplotlib is one of the most widely used data visualization libraries in Python. From simple to complex visualizations, it’s the go-to library for most. In this tutorial, we’ll take a look at how to plot a scatter plot in Matplotlib. Import Data We’ll be using the Ames Housing dataset and visualizing correlations between features from it. Let’s import Pandas and load in the dataset: import pandas as pd df = pd.read_csv(‘AmesHousing.csv’) Plot a Scatter Plot in Matplotlib Now, with […]

October 22, 2020 Python

Python: Slice Notation on String

Introduction The term slicing in programming usually refers to obtaining a substring, sub-tuple, or sublist from a string, tuple, or list respectively. Python offers an array of straightforward ways to slice not only these three but any iterable. An iterable is, as the name suggests, any object that can be iterated over. In this article, we’ll go over everything you need to know about Slicing Strings in Python. Slicing a String in Python There are a couple of ways to […]

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