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 […]

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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 […]

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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 […]

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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 […]

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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() […]

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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 […]

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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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Issue #104 – Using Test Sets to Evaluate Machine Translation

22 Oct20 Issue #104 – Using Test Sets to Evaluate Machine Translation Author: Dr. Karin Sim, Machine Translation Scientist @ Iconic Introduction There is finally a growing acceptance in some circles that evaluation of Machine Translation (MT) is lagging behind progress in Neural MT (NMT). Especially with regards to metrics such as BLEU, there is a recognition that “as NMT continues to improve, these metrics will inevitably lose their effectiveness” (Isabelle et al., 2017). In today’s blog post, we look […]

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6 Books on Ensemble Learning

Ensemble learning involves combining the predictions from multiple machine learning models. The effect can be both improved predictive performance and lower variance of the predictions made by the model. Ensemble methods are covered in most textbooks on machine learning; nevertheless, there are books dedicated to the topic. In this post, you will discover the top books on the topic of ensemble machine learning. After reading this post, you will know: Books on ensemble learning, including their table of contents and […]

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A holistic representation toward integrative AI

At Microsoft, we have been on a quest to advance AI beyond existing techniques, by taking a more holistic, human-centric approach to learning and understanding. As Chief Technology Officer of Azure AI Cognitive Services, I have been working with a team of amazing scientists and engineers to turn this quest into a reality. In my role, I enjoy a unique perspective in viewing the relationship among three attributes of human cognition: monolingual text (X), audio or visual sensory signals, (Y) […]

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