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Discarded Hard Drives: Data Science as Debugging
As a University professor, when setting data orientated projects to Computer Science undergraduates, I used to find it difficult to get students to interact properly with the data. Students tended to write programs to process the data, produce a couple of plots, but fail to develop any understanding of what... Read more
Background – How many cats does it take to identify a Cat? In this article, I cover the 12 types of AI problems i.e. I address the question : in which scenarios should you use Artificial Intelligence (AI)?  We cover this space in the  Enterprise AI course Some background: Recently, I conducted a... Read more
How the Multinomial Logistic Regression Model Works
In the pool of supervised classification algorithms, the logistic regression model is the first most algorithm to play with. This classification algorithm again categorized into different categories. These categories purely based on the number of target classes. If the logistic regression model used for addressing the binary classification kind of... Read more
How the Logistic Regression Model Works in Machine Learning
In this article, we are going to learn how the logistic regression model works in machine learning. The logistic regression model is one member of the supervised classification algorithm family. The building block concepts of logistic regression can be helpful in deep learning while building the neural networks. Logistic regression... Read more
Chapter 2: Machine Learning In the last chapter we were concerned with real-valued circuits that computed possibly complex expressions of their inputs (the forward pass), and also we could compute the gradients of these expressions on the original inputs (backward pass). In this chapter we will see how useful this... Read more
With the holidays long gone and likely everyone’s New Year’s resolutions along with it I figured I would spend some time working with data instead of working with gym weights.  Lacking any real inspiration, a friend pointed me to the University of California, Irvine’s Machine Learning data repository.  Specifically, he... Read more
Editor’s note: Opinions expressed in this post do not necessarily reflect the views of #ODSC At the start of this blog series I had no idea how the campaign dialogue would evolve.  I am surprised how the discussion has distanced even farther from issues to personal affairs leaving many Republicans to abandon Donald... Read more
Deutsch Credit Future Telling: part 2
To continue on this first path, it’s logical to proceed with hyperparameter tuning on the three algorithms previously mentioned in part 1. Here the Random Forest Classifier (R.F.C) pulls ahead with 77% accuracy while the other two are still around 75%. Where there were three on this road, there is... Read more
Classification tasks in Data Science come frequently, but the hardest are those with unbalanced classes. From biology to finance, the real-life situations are numerous. Before balancing your errors, establishing a baseline with the most frequent occurrence can give you over 90% accuracy right off the bat.  The question of whether... Read more
Intro to Natural Language Processing
Table of Contents 0.0 Setup 0.1 Python and Anaconda 0.2 Libraries 0.3 Other 1.0 Background 1.1 What is NLP? 1.2 Why is NLP Important? 1.3 Why is NLP a “hard” problem? 1.4 Glossary 2.0 Sentiment Analysis 2.1 Preparing the Data 2.1.1 Training Data 2.1.2 Test Data 2.2 Building a Classifier... Read more