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AI for Business

Exploring the Ethical Implications of AI: A Closer Look at the Challenges Ahead
This article discusses five common ethical issues that arise when AI is not implemented or released in the most responsible way.
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What is An AI Strategy and Why Every Business Needs One
This article discusses what an AI strategy means, the different types of AI strategies that you should know about, and how as a leader you can get…

What is AI Ethics?
This article is part of a series that will explore what AI ethics means, its implications to society, and how businesses can start leading the way by…

GPT-3: What is GPT-3 and what can it do for your business?
GPT-3 is a popular AI tool that everyone is raving about. What exactly is GPT-3 and what does it mean for your AI problems?
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What went wrong with Tay, the Twitter bot that turned racist?
Why Tay the Twitter bot from 2016 failed and what we can learn from it. How can we generalize this to ML development best practices?
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3 Strategic Mistakes Leaders Can Easily Avoid When Thinking About AI Integration
Rushing through AI integration can result in unintended failures. Learn 3 AI integration mistakes leaders can easily avoid to limit confusion, reduce waste, and truly reap the…
Technical Deep Dive for Practitioners

A Gentle Introduction to Deep Neural Networks with Python
This article examines the parts that make up neural networks and deep neural networks, as well as the fundamental different types of models (e.g. regression), their constituent parts (and how they contribute to model accuracy), and which…

FastText vs. Word2vec: A Quick Comparison
One of the questions that often comes up is what’s the difference between fastText and Word2Vec? Aren’t they both the same? Yes and no. They are conceptually the same, but there is a minor difference—fastText operates at a character…

Word2Vec: A Comparison Between CBOW, SkipGram & SkipGramSI
Word2Vec is a widely used word representation technique that uses neural networks under the hood. The resulting word representation or embeddings can be used to infer semantic similarity between words and phrases, expand queries, surface related concepts…

HashingVectorizer vs. CountVectorizer
Previously, we learned how to use CountVectorizer for text processing. In place of CountVectorizer, you also have the option of using HashingVectorizer. In this tutorial, we will learn how HashingVectorizer differs from CountVectorizer and when to use…

10+ Examples for Using CountVectorizer
Scikit-learn’s CountVectorizer is used to transform a corpora of text to a vector of term / token counts. It also provides the capability to preprocess your text data prior to generating the vector representation making it a…

Build Your First Text Classifier in Python with Logistic Regression
Text classification is the automatic process of predicting one or more categories given a piece of text. For example, predicting if an email is legit or spammy. Thanks to Gmail’s spam classifier, I don’t see or hear…