Tag: linear regression

Cheat Sheet – 10 Machine Learning Algorithms & R Commands

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From Bytes Cravings: “This article lists down 10 popular machine learning algorithms and related R commands (& package information) that could be used to create respective models. The objective is to represent a quick reference page for beginners/intermediate level R programmers who are working on machine learning related problems…. Following are the different ML algorithms included in this article: Linear Regression Logistic Regression K-Means Clustering K-Nearest Neighbors (KNN) Classification Naive … Continue Reading

Learn Data Science

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From GitHub: “A collection of Data Science Learning materials in the form of iPython Notebooks. Associated data sets. The initial beta release consists of four major topics Linear Regression Logistic Regression Random Forests K-Means Clustering Each of the above has at least three iPython Notebooks covering Overview (an exposition of the technique for the math-wary) Data Exploration (the nuts and bolts of real world data wrangling) Analysis (using the technique to … Continue Reading

Essentials of Machine Learning Algorithms (with Python and R Codes)

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From Analytics Vidhya: “Today, as a data scientist, I can build data crunching machines with complex algorithms for a few dollors per hour. But, reaching here wasn’t easy! I had my dark days and nights…. The idea behind creating this guide is to simplify the journey of aspiring data scientists and machine learning enthusiasts across the world. Through this guide, I will enable you to work on machine learning problems and … Continue Reading

Bivariate Linear Regression

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from datascience+: “Regression is one of the – maybe even the single most important fundamental tool for statistical analysis in quite a large number of research areas. It forms the basis of many of the fancy statistical methods currently en vogue in the special sciences. Multilevel analysis and structural equation modeling are perhaps the most widespread and most obvious extensions of regression analysis that are applied in a large chunk of current … Continue Reading

Correlation and Linear Regression

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From datascience+: “Before going into complex model building, looking at data relation is a sensible step to understand how your different variables interact together. Correlation looks at trends shared between two variables, and regression looks at relation between a predictor (independent variable) and a response (dependent) variable.”

Python for Data Science and Machine Learning Bootcamp

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From Udemy: “Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more! What Will I Learn? Use Python for Data Science and Machine Learning Use Spark for Big Data Analysis Implement Machine Learning Algorithms Learn to use NumPy for Numerical Data Learn to use Pandas for Data Analysis Learn to use Matplotlib for Python Plotting Learn to use Seaborn for statistical plots Use Plotly for interactive … Continue Reading

SAS Learning path and resources – Business Analyst in SAS

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This is a curriculum compiled by Analytics Vidhya as a guide to learning SAS for business analytics. The curriculum is composed of the following steps: Step 0: Why learn SAS Step 1: Downloading and Installing SAS Step 2: Base SAS on sas.com Step 3: SQL Step 4: Descriptive Statistics with the Udacity Intro to Descriptive Statistics course Step 5: Inferential Statistics with the Udacity Intro to Inferential Statistics course Step … Continue Reading

Learn Data Science

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Learn Data Science is “a collection of Data Science Learning materials in the form of iPython Notebooks” and the “associated data sets.” The following topics are covered, with at least three notebooks including an Overview – an exposition of the technique for the math-wary”, Data Exploration – “the nuts and bolts of real world data wrangling”, and Analysis – “using the technique to get results”. Topics: Linear Regression Logistic Regression … Continue Reading

Data Science from Scratch: First Principles with Python

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From Amazon: “Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get … Continue Reading

Linear Regression and Modeling

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This is course 3 of 5 in the Statistics with R Specialization. From Coursera: “This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics … Continue Reading