Tags

AI: 1 Agile Framework: 1 Amadeus: 1 Anomaly Detection: 1 BI: 1 BSPF: 3 Backtesting: 3 Business Understanding: 11 CRISP-DM: 2 CRM: 1 Case Study: 1 Cheatsheet: 2 Churn: 5 Code: 1 Community Detection: 3 Customer Analytics: 1 Customer Segmentation: 3 DALEX: 1 DMAIC: 1 DS4B: 5 DS4B 201-R: 13 Data Mining: 1 Data Science: 17 Data Science For Business: 1 Data Science Team: 1 Deep Learning: 3 EARL: 2 Education: 1 Employee Attrition: 2 Employee Turnover: 6 Excel: 1 Expected Value: 2 Financial Analysis: 1 Framework: 1 GGally: 2 Getting Started: 1 H2O: 3 HR 201: 1 HR Analytics: 6 Human Resources: 4 IML: 1 InfoSec: 1 Kaggle Competitions: 1 Keras: 2 LIME: 1 Learning Data Science: 2 MBA: 1 Machine Learning: 1 Marketing: 2 Monte Carlo: 1 Multiple Cores: 2 Neural Network: 1 PCA: 1 Parallel Processing: 3 Partnerships: 1 People Analytics: 4 PerformanceAnalytics: 2 Principles By Ray Dalio: 1 Product Backorders: 1 Project Management: 2 Python: 5 Quandl: 2 Quantopian: 1 R: 76 R-Project: 76 RMarkdown: 2 SQL: 1 Sales Analytics: 1 Sales Data Scientist: 1 Salesforce: 1 Scikit-Learn: 1 Shiny: 2 Simulation: 1 Stock Analysis: 10 Strategy: 1 TTR: 8 TensorFlow: 3 Text Analysis: 1 Tidyverse: 2 Time Series: 4 Trading Algorithms: 1 Trading Strategy: 7 Web Scraping: 3 Zipline: 1 alphavantager: 1 anomalize: 2 bikes data set: 4 broom: 2 caret: 1 corrplot: 1 corrr: 4 cowplot: 1 cranlogs: 4 dalex: 1 dplyr: 8 dygraphs: 1 flyingfox: 1 forecast: 1 fs: 1 furrr: 1 ggplot2: 5 h2o: 11 igraph: 1 iml: 1 keras: 4 kmeans: 1 lime: 7 matplotlib: 1 multidplyr: 2 networkD3: 1 orderSimulatoR: 1 padr: 1 pandas: 1 parallel: 2 pdp: 1 plotly: 2 prcomp: 1 purrr: 2 quantmod: 8 r-finance: 1 radix: 1 recipes: 6 reticulate: 1 rsample: 3 rvest: 3 scikit-learn: 1 seaborn: 1 silhouette: 1 skimr: 3 sweep: 3 tibbletime: 8 tidyquant: 18 tidyr: 5 tidyverse: 18 timekit: 4 timekitr: 1 timetk: 5 vip: 1 xts: 9 yardstick: 3 zoo: 8

AI

Agile Framework For Creating An ROI-Driven Data Science Practice

Agile Framework

Agile Framework For Creating An ROI-Driven Data Science Practice

Amadeus

Case Study: How To Build A High Performance Data Science Team

Anomaly Detection

Information Security: Anomaly Detection and Threat Hunting with Anomalize

BI

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

BSPF

Data Science With R Course Series - Week 1

Agile Framework For Creating An ROI-Driven Data Science Practice

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

Backtesting

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Business Understanding

Marketing Analytics - Fast-Food Promotion Effectiveness

Data Science With R Course Series - Week 10

Data Science With R Course Series - Week 9

Data Science With R Course Series - Week 8

Data Science With R Course Series - Week 7

Marketing Analytics and Data Science

Data Science With R Course Series - Week 6

Data Science With R Course Series - Week 5

Data Science With R Course Series - Week 4

Data Science With R Course Series - Week 3

Data Science With R Course Series - Week 2

CRISP-DM

Agile Framework For Creating An ROI-Driven Data Science Practice

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

CRM

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

Case Study

Case Study: How To Build A High Performance Data Science Team

Cheatsheet

Ultimate Python Cheatsheet: Data Science Workflow with Python

New R Cheatsheet: Data Science Workflow with R

Churn

Interpretable Machine Learning Algorithms with Dalex and H2O

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Understand Employee Churn Using H2O Machine Learning and Lime

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

Code

A Data Scientist's Resources

Community Detection

Customer Segmentation Part 3: Network Visualization

Customer Segmentation Part 2: PCA for Segment Visualization

Customer Segmentation Part 1: K Means Clustering

Customer Analytics

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

Customer Segmentation

Customer Segmentation Part 3: Network Visualization

Customer Segmentation Part 2: PCA for Segment Visualization

Customer Segmentation Part 1: K Means Clustering

DALEX

Interpretable Machine Learning Algorithms with Dalex and H2O

DMAIC

Agile Framework For Creating An ROI-Driven Data Science Practice

DS4B

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Interpretable Machine Learning Algorithms with Dalex and H2O

Understand Employee Churn Using H2O Machine Learning and Lime

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

DS4B 201-R

Marketing Analytics - Fast-Food Promotion Effectiveness

Data Science Course Savings Extended: Get 35% OFF Through Cyber Monday

Black Friday 35% Off: Data Science With R Course

Data Science With R Course Series - Week 10

Data Science With R Course Series - Week 9

Data Science With R Course Series - Week 8

Data Science With R Course Series - Week 7

Data Science With R Course Series - Week 6

Data Science With R Course Series - Week 5

Data Science With R Course Series - Week 4

Data Science With R Course Series - Week 3

Data Science With R Course Series - Week 2

Data Science With R Course Series - Week 1

Data Mining

orderSimulatoR: Simulate Orders for Business Analytics

Data Science

Marketing Analytics - Fast-Food Promotion Effectiveness

Data Science Course Savings Extended: Get 35% OFF Through Cyber Monday

Black Friday 35% Off: Data Science With R Course

Data Science With R Course Series - Week 10

Data Science With R Course Series - Week 9

Data Science With R Course Series - Week 8

Data Science With R Course Series - Week 7

Marketing Analytics and Data Science

Data Science With R Course Series - Week 6

Data Science With R Course Series - Week 5

Data Science With R Course Series - Week 4

Data Science With R Course Series - Week 3

Data Science With R Course Series - Week 2

Data Science With R Course Series - Week 1

Agile Framework For Creating An ROI-Driven Data Science Practice

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

Data Science For Business

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

Data Science Team

Case Study: How To Build A High Performance Data Science Team

Deep Learning

Time Series Analysis for Business Forecasting with Artificial Neural Networks

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

EARL

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

Business Science EARL SF 2017 Presentation: tidyquant, timekit, and more!

Education

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

Employee Attrition

Interpretable Machine Learning Algorithms with Dalex and H2O

Understand Employee Churn Using H2O Machine Learning and Lime

Employee Turnover

Interpretable Machine Learning Algorithms with Dalex and H2O

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Understand Employee Churn Using H2O Machine Learning and Lime

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

HR Analytics: Using Machine Learning to Predict Employee Turnover

Excel

A Data Scientist's Resources

Expected Value

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Financial Analysis

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Framework

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

GGally

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

Getting Started

Data Science With R Course Series - Week 1

H2O

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Interpretable Machine Learning Algorithms with Dalex and H2O

HR 201

Data Science For Business: Course Now Open!

HR Analytics

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

Human Resources

Interpretable Machine Learning Algorithms with Dalex and H2O

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Understand Employee Churn Using H2O Machine Learning and Lime

IML

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

InfoSec

Information Security: Anomaly Detection and Threat Hunting with Anomalize

Kaggle Competitions

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Keras

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

LIME

Understand Employee Churn Using H2O Machine Learning and Lime

Learning Data Science

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

6 Reasons To Learn R For Business

MBA

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

Machine Learning

Agile Framework For Creating An ROI-Driven Data Science Practice

Marketing

Marketing Analytics and Data Science

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

Monte Carlo

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Multiple Cores

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

Speed Up Your Code: Parallel Processing with multidplyr

Neural Network

Time Series Analysis for Business Forecasting with Artificial Neural Networks

PCA

Customer Segmentation Part 2: PCA for Segment Visualization

Parallel Processing

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

Speed Up Your Code: Parallel Processing with multidplyr

Partnerships

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

People Analytics

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

PerformanceAnalytics

tidyquant: New Tools for Performing Financial Analysis within the Tidy Ecosystem

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Principles By Ray Dalio

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

Product Backorders

Predictive Sales Analytics: Use Machine Learning to Predict and Optimize Product Backorders

Project Management

Agile Framework For Creating An ROI-Driven Data Science Practice

How To Successfully Manage A Data Science Project For Businesses: The Business Science Problem Framework

Python

Ultimate Python Cheatsheet: Data Science Workflow with Python

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Case Study: How To Build A High Performance Data Science Team

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

A Data Scientist's Resources

Quandl

tidyquant 0.5.0: select, rollapply, and Quandl

tidyquant Integrates Quandl: Getting Data Just Got Easier

Quantopian

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

R

Marketing Analytics - Fast-Food Promotion Effectiveness

Time Series Analysis for Business Forecasting with Artificial Neural Networks

Data Science Course Savings Extended: Get 35% OFF Through Cyber Monday

Black Friday 35% Off: Data Science With R Course

Data Science With R Course Series - Week 10

Data Science With R Course Series - Week 9

Data Science With R Course Series - Week 8

New R Cheatsheet: Data Science Workflow with R

Data Science With R Course Series - Week 7

Marketing Analytics and Data Science

Data Science With R Course Series - Week 6

Data Science With R Course Series - Week 5

Data Science With R Course Series - Week 4

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Data Science With R Course Series - Week 3

Data Science With R Course Series - Week 2

Data Science With R Course Series - Week 1

Case Study: How To Build A High Performance Data Science Team

Agile Framework For Creating An ROI-Driven Data Science Practice

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Interpretable Machine Learning Algorithms with Dalex and H2O

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Understand Employee Churn Using H2O Machine Learning and Lime

Information Security: Anomaly Detection and Threat Hunting with Anomalize

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Anomaly Detection Using Tidy and Anomalize

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

The Tidy Time Series Platform: tibbletime 0.1.0

6 Reasons To Learn R For Business

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

Demo Week: Time Series Machine Learning with h2o and timetk

Demo Week: Tidy Time Series Analysis with tibbletime

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

Demo Week: Tidy Forecasting with sweep

Demo Week: Time Series Machine Learning with timetk

Demo Week: class(Monday) <- tidyquant

Predictive Sales Analytics: Use Machine Learning to Predict and Optimize Product Backorders

It's tibbletime v0.0.2: Time-Aware Tibbles, New Functions, Weather Analysis and More

HR Analytics: Using Machine Learning to Predict Employee Turnover

It's tibbletime: Time-Aware Tibbles

alphavantager: An R interface to the Free Alpha Vantage Financial Data API

Tidy Time Series Analysis, Part 4: Lags and Autocorrelation

Tidy Time Series Analysis, Part 3: The Rolling Correlation

BizSci Package Updates: Formerly timekit... Now timetk :)

Tidy Time Series Analysis, Part 2: Rolling Functions

sweep: Extending broom for time series forecasting

Tidy Time Series Analysis, Part 1

Business Science EARL SF 2017 Presentation: tidyquant, timekit, and more!

tidyquant: R/Finance 2017 Presentation

timekit: New Documentation, Function Improvements, Forecasting Vignette

tidyquant: New Tools for Performing Financial Analysis within the Tidy Ecosystem

timekit: Time Series Forecast Applications Using Data Mining

tidyquant 0.5.0: select, rollapply, and Quandl

tidyquant Integrates Quandl: Getting Data Just Got Easier

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

Speed Up Your Code: Parallel Processing with multidplyr

Russell 2000 Quantitative Stock Analysis in R: Six Stocks with Amazing, Consistent Growth

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Customer Segmentation Part 3: Network Visualization

Customer Segmentation Part 2: PCA for Segment Visualization

Customer Segmentation Part 1: K Means Clustering

orderSimulatoR: Simulate Orders for Business Analytics

A Data Scientist's Resources

R-Project

Marketing Analytics - Fast-Food Promotion Effectiveness

Time Series Analysis for Business Forecasting with Artificial Neural Networks

Data Science Course Savings Extended: Get 35% OFF Through Cyber Monday

Black Friday 35% Off: Data Science With R Course

Data Science With R Course Series - Week 10

Ultimate Python Cheatsheet: Data Science Workflow with Python

Data Science With R Course Series - Week 9

Data Science With R Course Series - Week 8

New R Cheatsheet: Data Science Workflow with R

Data Science With R Course Series - Week 7

Marketing Analytics and Data Science

Data Science With R Course Series - Week 6

Data Science With R Course Series - Week 5

Data Science With R Course Series - Week 4

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Data Science With R Course Series - Week 3

Data Science With R Course Series - Week 2

Data Science With R Course Series - Week 1

Case Study: How To Build A High Performance Data Science Team

Agile Framework For Creating An ROI-Driven Data Science Practice

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Interpretable Machine Learning Algorithms with Dalex and H2O

Press Release: Business Science Partners With Method Data Science To Accelerate Your Data Science Career

New Course Content: DS4B 201 Chapter 7, The Expected Value Framework For Modeling Churn With H2O

Data Science for Business: 3 Reasons Why You Need the Expected Value Framework

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Understand Employee Churn Using H2O Machine Learning and Lime

Information Security: Anomaly Detection and Threat Hunting with Anomalize

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Anomaly Detection Using Tidy and Anomalize

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

The Tidy Time Series Platform: tibbletime 0.1.0

6 Reasons To Learn R For Business

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

Demo Week: Time Series Machine Learning with h2o and timetk

Demo Week: Tidy Time Series Analysis with tibbletime

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

Demo Week: Tidy Forecasting with sweep

Demo Week: Time Series Machine Learning with timetk

Demo Week: class(Monday) <- tidyquant

Predictive Sales Analytics: Use Machine Learning to Predict and Optimize Product Backorders

It's tibbletime v0.0.2: Time-Aware Tibbles, New Functions, Weather Analysis and More

HR Analytics: Using Machine Learning to Predict Employee Turnover

It's tibbletime: Time-Aware Tibbles

alphavantager: An R interface to the Free Alpha Vantage Financial Data API

Tidy Time Series Analysis, Part 4: Lags and Autocorrelation

Tidy Time Series Analysis, Part 3: The Rolling Correlation

BizSci Package Updates: Formerly timekit... Now timetk :)

Tidy Time Series Analysis, Part 2: Rolling Functions

sweep: Extending broom for time series forecasting

Tidy Time Series Analysis, Part 1

Business Science EARL SF 2017 Presentation: tidyquant, timekit, and more!

tidyquant: R/Finance 2017 Presentation

timekit: New Documentation, Function Improvements, Forecasting Vignette

tidyquant: New Tools for Performing Financial Analysis within the Tidy Ecosystem

timekit: Time Series Forecast Applications Using Data Mining

tidyquant 0.5.0: select, rollapply, and Quandl

tidyquant Integrates Quandl: Getting Data Just Got Easier

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

Speed Up Your Code: Parallel Processing with multidplyr

Russell 2000 Quantitative Stock Analysis in R: Six Stocks with Amazing, Consistent Growth

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Customer Segmentation Part 3: Network Visualization

Customer Segmentation Part 2: PCA for Segment Visualization

Customer Segmentation Part 1: K Means Clustering

orderSimulatoR: Simulate Orders for Business Analytics

RMarkdown

New R Cheatsheet: Data Science Workflow with R

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

SQL

A Data Scientist's Resources

Sales Analytics

Predictive Sales Analytics: Use Machine Learning to Predict and Optimize Product Backorders

Sales Data Scientist

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

Salesforce

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

Scikit-Learn

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Shiny

New R Cheatsheet: Data Science Workflow with R

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Simulation

orderSimulatoR: Simulate Orders for Business Analytics

Stock Analysis

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

tidyquant 0.5.0: select, rollapply, and Quandl

tidyquant Integrates Quandl: Getting Data Just Got Easier

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

Russell 2000 Quantitative Stock Analysis in R: Six Stocks with Amazing, Consistent Growth

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Strategy

Marketing Strategy: Why MBAs Can Benefit from Learning Analytics

TTR

Tidy Time Series Analysis, Part 3: The Rolling Correlation

Tidy Time Series Analysis, Part 2: Rolling Functions

tidyquant: New Tools for Performing Financial Analysis within the Tidy Ecosystem

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

TensorFlow

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Text Analysis

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

Tidyverse

New R Cheatsheet: Data Science Workflow with R

R and Python: How to Integrate the Best of Both into Your Data Science Workflow

Time Series

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Information Security: Anomaly Detection and Threat Hunting with Anomalize

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Anomaly Detection Using Tidy and Anomalize

Trading Algorithms

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

Trading Strategy

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

Russell 2000 Quantitative Stock Analysis in R: Six Stocks with Amazing, Consistent Growth

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Web Scraping

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

Russell 2000 Quantitative Stock Analysis in R: Six Stocks with Amazing, Consistent Growth

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

Zipline

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

alphavantager

alphavantager: An R interface to the Free Alpha Vantage Financial Data API

anomalize

Information Security: Anomaly Detection and Threat Hunting with Anomalize

Anomaly Detection Using Tidy and Anomalize

bikes data set

Customer Segmentation Part 3: Network Visualization

Customer Segmentation Part 2: PCA for Segment Visualization

Customer Segmentation Part 1: K Means Clustering

orderSimulatoR: Simulate Orders for Business Analytics

broom

sweep: Extending broom for time series forecasting

tidyquant Integrates Quandl: Getting Data Just Got Easier

caret

Understand Employee Churn Using H2O Machine Learning and Lime

corrplot

Quantitative Stock Analysis Tutorial: Screening the Returns for Every S&P500 Stock in Less than 5 Minutes

corrr

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

Tidy Time Series Analysis, Part 3: The Rolling Correlation

Tidy Time Series Analysis, Part 2: Rolling Functions

tidyquant Integrates Quandl: Getting Data Just Got Easier

cowplot

Tidy Time Series Analysis, Part 3: The Rolling Correlation

cranlogs

Tidy Time Series Analysis, Part 4: Lags and Autocorrelation

Tidy Time Series Analysis, Part 3: The Rolling Correlation

Tidy Time Series Analysis, Part 2: Rolling Functions

Tidy Time Series Analysis, Part 1

dalex

Interpretable Machine Learning Algorithms with Dalex and H2O

dplyr

New R Cheatsheet: Data Science Workflow with R

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

Speed Up Your Code: Parallel Processing with multidplyr

dygraphs

Recreating RView's ''Reproducible Finance With R: Sector Correlations''

flyingfox

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

forecast

sweep: Extending broom for time series forecasting

fs

How To Learn R, Part 1: Learn From A Master Data Scientist's Code

furrr

Algorithmic Trading: Using Quantopian's Zipline Python Library In R And Backtest Optimizations By Grid Search And Parallel Processing

ggplot2

New R Cheatsheet: Data Science Workflow with R

tidyquant 0.4.0: PerformanceAnalytics, Improved Documentation, ggplot2 Themes and More

tidyquant 0.3.0: ggplot2 Enhancements, Real-Time Data, and More

tidyquant 0.2.0: Added Functionality for Financial Engineers and Business Analysts

tidyquant: Bringing Quantitative Financial Analysis to the tidyverse

h2o

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

Kaggle Competition In 30 Minutes: Predict Home Credit Default Risk With R

Interpretable Machine Learning Algorithms with Dalex and H2O

Understand Employee Churn Using H2O Machine Learning and Lime

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

Demo Week: Time Series Machine Learning with h2o and timetk

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

Predictive Sales Analytics: Use Machine Learning to Predict and Optimize Product Backorders

HR Analytics: Using Machine Learning to Predict Employee Turnover

igraph

Customer Segmentation Part 3: Network Visualization

iml

IML and H2O: Machine Learning Model Interpretability And Feature Explanation

keras

Time Series Analysis for Business Forecasting with Artificial Neural Networks

Time Series Analysis: KERAS LSTM Deep Learning - Part 2

Time Series Analysis: KERAS LSTM Deep Learning - Part 1

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

kmeans

Customer Segmentation Part 1: K Means Clustering

lime

Understand Employee Churn Using H2O Machine Learning and Lime

Data Science For Business: Course Now Open!

Data Science For Business: Course Launch In 5 Days!!!

Customer Analytics: Using Deep Learning With Keras To Predict Customer Churn

EARL Presentation on HR Analytics: Using ML to Predict Employee Turnover

LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover

HR Analytics: Using Machine Learning to Predict Employee Turnover

matplotlib

Ultimate Python Cheatsheet: Data Science Workflow with Python

multidplyr

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

Speed Up Your Code: Parallel Processing with multidplyr

networkD3

Customer Segmentation Part 3: Network Visualization

orderSimulatoR

orderSimulatoR: Simulate Orders for Business Analytics

padr

timekit: Time Series Forecast Applications Using Data Mining

pandas

Ultimate Python Cheatsheet: Data Science Workflow with Python

parallel

Speed Up Your Code Part 2: Parallel Processing Financial Data with multidplyr + tidyquant

Speed Up Your Code: Parallel Processing with multidplyr

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