One common issue with python programming is the need to use passwords, API keys, or other credentials in python code. However, you do not want to make these passwords, keys, and credentials public. So, using[…]
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Category: Data Analysis
Artificial Neural Network Disadvantages
Artificial Neural Networks (ANNs) can solve an extremely wide variety of problems, including virtually any problem reduceable to functions. Often ANNs are used to obtain forecasts, validate data, detect anomolies, research customer purchases, and manage[…]
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Underspecification in AI
Underspecification is the failure to specify in enough detail, according to Wiktionary. In machine learning and AI, the underspecification of training samples can result in vastly different predictions for edge cases, even when very similar[…]
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Getting Data Outside D3 or Plotly CSV Functions
D3 and plotly.js are two of the main graphing tools for web applications. They can get data from JSON strings or files, CSV files, or TSV files. However, one problem that was very difficult to[…]
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Racism and Gender Bias in Machine Learning, Fixes not Always Easy
Racism and gender bias can easily and inadvertently infect machine learning algorithms. One prime example examined what job applicants were most likely to be hired. However, bias is inherent in any decision-making system that involves[…]
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Dynamic Plotly.js Plot with Menu
Plotly.js allows for dynamic plots. However, event handlers are needed to make the graphs dynamic. For complete customization of active plots, you would likely need D3, but I will not cover D3 in this tutorial.To[…]
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Plotly.js Titles and Labels
Part II of the Plotly.js Tutorial Series Covers Plotly.js Titles and Axis LabelsBy default, Plotly.js plots are sized with the minimum and maximum X and Y values as the entire range. This default can often[…]
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Basic Plotly.js Plots
Data visualization is an essential aspect of communicating with data. Plotly, a graphing module that can work with Python, also has a javascript version. With plotly.js, making web-based dashboards and dynamic graphs is straight forward.As[…]
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Cross Validation and Model Scoring with Sklearn
Machine Learning Tutorial Part IIIOne of the most important aspects of machine learning is choosing the best model. The easiest way to pick among a list of models is to make each model instance a[…]
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Train_test_split with Sklearn
Machine Learning Tutorial part IIAfter you evaluate the scores for each column, select the columns with the highest scores. These columns should be ‘displacement’, ‘horsepower’, and ‘weight’. In this case, they will be columns 2,[…]
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