# Sang Lee

Follow## Magazines

## Flips

# These are the best books for learning modern statistics—and they’re all free

# Video: How to run R and Python in SQL Server from a Jupyter notebook

# Tidying messy Excel data (tidyxl)

# Top 5 Best Data Visualisation Libraries In Python

# A guide to working with character data in R

# Open Source Datasets with Kaggle

# Statistical Significance Tests for Comparing Machine Learning Algorithms

# Dear data scientists, how to ease your job

# It’s that easy! Image classification with keras in roughly 100 lines of code.

# April 2018: “Top 40” New Packages

# A Comparative Review of the RKWard GUI for R

# How Many Factors to Retain in Factor Analysis

# Context Compatibility in Data Analysis

# An Overview of Recommendation Systems

# Basic Database Interaction-Python

# ML models: What they can’t learn?

# Big Data with R

# Introduction to Machine Learning for non-developers

# R and Python are joining forces, in the most ambitious crossover event of the year—for programmers

# Big changes behind the scenes in R 3.5.0

# An Introduction to Greta

# Yet Another Caret Workshop

# How do I interpret the AIC

# Regular Expressions Every R programmer Should Know

# Introducing TensorFlow Probability

# Weighted survey data with Power BI compared to dplyr, SQL or survey by @ellis2013nz

# autoEDA - Automated exploratory data analysis

# Jupyter Notebook for Beginners: A Tutorial