We introduce you to the big world of recommender systems. We cover what they are, why they are important, and how they work. We also go over how and why big companies like Amazon, Netflix, Pandora, and YouTube rely on …
Redshift, MySQL, PostGreSQL, Hadoop and a list of other data systems are utilized for various analytical and operational purposes in the modern business world. As each company focuses more and more on big data the importance of picking the right …
This talk is an introduction to Natural Language Processing (NLP) and its parent areas of Artificial Intelligence and Linguistics. We will discuss real use-cases of NLP in the world today – starting with the core technology, and how that core …
In this webinar, we will explore what is a data engineer. This includes discussing what are the goals, skills, and tools that they use on a daily basis. We wanted to take a moment to provide insights to the other …
In part 3 of this video series, learn how to evaluate time series model predictions using mean absolute error and Python’s statistics and matplotlib packages. We look at plotting the differences between actual versus predicted values, and calculate the mean …
In part 2 of this video series, learn how to build an ARIMA time series model using Python’s statsmodels package and predict or forecast N timestamps ahead into the future. Now that we have differenced our data to make it …
In part 1 of this video series, learn how to read and index your data for time series using Python’s pandas package. We check if the data meets the requirements or assumptions for time series modeling by plotting to see …
In this quick overview, we introduce you to the concepts of one-versus-one and one-versus-all in classification. In classification models, you will often want to predict one class from another. This is called binary classification, or one-versus-one. But what if you …
In this quick tutorial, we learn that machines can not only make sense of words but also make sense of words in their context. N-grams are one way to help machines understand a word in its context by looking at …
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to …
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