# Tag: logistic regression

### Enterprise Data World

Conferences / Gatherings and OrganizationsNext Event: April 27-28, 2018 San Francisco, CA “The 21st Annual Enterprise Data World (EDW) Conference is recognized as the most comprehensive educational conference ondata management in the world. Your Transformation to Data-Driven Business Starts Here!” 2018 Registration Videos from previous conferences

### Python for Data Science and Machine Learning Bootcamp

Courses / Self-paced online courseFrom 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

### Spark and Python for Big Data with PySpark

Courses / Self-paced online courseFrom Udemy: “Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more! What Will I Learn? Use Python and Spark together to analyze Big Data Learn how to use the new Spark 2.0 DataFrame Syntax Work on Consulting Projects that mimic real world situations! Classify Customer Churn with Logistic Regression Use Spark with Random Forests for Classification Learn now to use Spark’s Gradient Boosted … Continue Reading

### SAS Learning path and resources – Business Analyst in SAS

Curricula / References, Learning Guides, Etc.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

Curricula / References, Learning Guides, Etc.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

Books / physical books or multiple formatsFrom 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

### DataCamp – Credit Risk Modeling in R

Courses / Interactive tutorial style courseFrom DataCamp: “This hands-on-course with real-life credit data will teach you how to model credit risk by using logistic regression and decision trees in R. Modeling credit risk for both personal and company loans is of major importance for banks. The probability that a debtor will default is a key component in getting to a measure for credit risk. While introducing other models in this course as well, we focus on … Continue Reading

### Machine Learning Cheat Sheet

Books / Cheat Sheets / Free eBooks / References, Learning Guides, Etc.This cheat sheet contains many classical equations and diagrams on machine learning, which will help you quickly recall knowledge and ideas in machine learning.

### The Elements of Statistical Learning

Books / physical books or multiple formatsThis book describes the important ideas in statistics, data mining, machine learning, and bioinformatics in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.

### The Analytics Edge

Courses / Scheduled online course / Self-paced online courseThrough inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.

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