Learn Data Science

“Learn Data Science” delves into the realm of data science, exploring topics like Python programming speed, AI applications with short-term memory, and machine learning model augmentation. The document discusses the importance of understanding the speed of Python, the role of short-term memory in AI applications, and the significance of data augmentation in machine learning models. It touches on concepts like development time versus run time bottlenecks, maintaining conversation history in databases, and the challenges of treating data as static in a dynamic world of big data. The content provides insights into optimizing Python programming, enhancing AI applications, and improving machine learning model performance.

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II. Data Cleanup

Learn Data Science

II. Data Cleanup We find the data are "messy" i.e aren't cleanly prepared for import - for instance numeric columns might have some strings in them. This is very common in raw data especially that obt...

Random Forests - Analysis.

Learn Data Science

Random Forests - Analysis. Introduction Our goal for this phase is to use the reduced variable data set from our exploration phase to create a model predicting human activity, using Random Forests. To...

Before you begin

Learn Data Science

Before you begin About the content The content for Learn Data Science beta is written in IPython Notebook. This is a technology that allows executable code to be run via a browser with the results vis...

Linear Regression - Analysis

Learn Data Science

Linear Regression - Analysis We're going to pick up where we left off at the end of the exploration and define a linear model with two independent variables determining the dependent variable, Interes...

Linear Regression - Overview

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Linear Regression - Overview How can I make predictions about real-world quantities, like sales or life expectancy? Most often in real world applications we need to understand how one variable is dete...

Linear Regression Data Exploration: Lending Club

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Linear Regression Data Exploration: Lending Club How can I predict interest rates based on borrower and loan attributes? The Lending Club is a peer-to-peer lending site where members make loans to eac...

Learn Data Science

This is a placeholder. The data set used is the same as in Linear Regression where the data exploration was done in depth. So this section is just a place holder and the content is identical to the da...

Logistic Regression - Overview

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Logistic Regression - Overview What are the odds that an event will happen? Answering yes/no questions. Often we have to resolve questions with binary or yes/no outcomes. For example: Does a patient h...

Logistic Regression - Analysis

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Logistic Regression - Analysis Introduction We're going to look at the same data set from Lending Club but ask a different question. One that has a binary outcome. Let's assume we have a FICO Score of...

Threshold functions for logistic regression

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Threshold functions for logistic regression Odds, mathematically speaking. We are going to take the notion of odds, put a simple mathematical framework around it and then use our previous knowledge of...

Random Forests - Overview

Learn Data Science

Random Forests - Overview How do I handle data when the number of variables is very high? Often a problem that needs to be tackled is so large or complex that we need a group of experts not just a sin...

data exploration

Learn Data Science

data exploration data analysis