Eric Kleppen
Software Product Analyst at Infinite Campus
Expertise: Software Engineering
Education: University of Minnesota

Eric Kleppen is a software product analyst at Infinite Campus, where he’s worked since 2012 in a number of roles. Eric earned his bachelor’s degree in scientific and technical communication from the University of Minnesota. He also holds a certificate in data visualization and data analysis from the University of Minnesota.

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8 Articles
Sentiment analysis illustration of three people who each have an emoji-like speech bubble over their head. From left to right they're neutral, happy, and sad.
We use sentiment analysis to gain insights into a target audience’s feelings about a particular topic. Here are the basics of sentiment analysis types and techniques.
Turing Test image of a man from behind having a conversation with a white humanoid robot.
In the Turing Test, a computer and human are asked questions to determine which is human. The computer passes if it is indistinguishable from the human. Here’s how the test works, a brief history, variations, limitations and how it’s used today.
Hypervisor data storage towers
A hypervisor is software that allocates a computer’s hardware resources among virtual machines (VMs), allowing multiple VMs to run simultaneously on a single physical machine. Here's how they work, their types, benefits and risks.
linux-vm
A virtual machine is like having a computer inside your computer. Here’s how to create your own Linux VM.
how-to-find-the-variance
Variance is a measurement of how far values in a data set differ from the mean. Here’s how to calculate variance by hand or in Python.
NLP-for-beginners
Want to practice NLP? Here’s how to use Python to start collecting text through APIs and web scraping.
nlp
Explore concrete ways to apply preprocessing, tokenization, vectorization and feature engineering on text data with these 3 projects.
nlp-word2vec-python
Word2vec is a natural language processing (NLP) technique used to represent words as vectors, where vectors close together in the vector space indicate they have similar contexts. Here's how to vectorize text using word2vec, Gensim and Plotly.