Azure ML: Deploying Recommenders

Python Data Science: Automating Cleaning: Dropping Rows Versus Columns when Addressing Missing Data

Python Data Science: Automating Cleaning: Addressing Skewness with Math Transformations

Python Data Science: Automating Cleaning: Managing Outliers All-Features-At-Once DBSCAN clustering

Python Data Science: Automating Cleaning: Managing Outliers One-Feature-At-A-Time

Python Data Science: Automating Cleaning: Bin Low Count Categorical Groups

Python Data Science: Automating Cleaning: Parsing Dates

Python Data Science: Automating Cleaning: Data Wrangling: Empty, Single Value, Primary Key columns

Python Data Science: Automating EDA: Bivariate Relationships: Part 5: Add your functions to .py

Python Data Science: Automating EDA: Bivariate Relationships: Part 4: Including group comparisons

Python Data Science: Automating EDA: Bivariate Relationships: Part 3: Choosing the best correlation

Python Data Science: Automating EDA: Bivariate Relationships: Part 2: Visualizations

Python Data Science: Automating EDA: Bivariate Relationships: Part 1: Basic statistics summary

Python Data Science: Automating EDA: Univariate Statistics and Visualizations

API with headers in Python: Polygon.io stock market data

Tableau: Forecasting

Tableau: Building Dashboards

Tableau: Advanced Filtering Top and Bottom 10

Tableau: Line and Area Charts (data over time)

Tableau: Geography map

Tableau: Heatmaps, 2 dimensions

Tableau: Scatterplots, 2 measures

Tableau: Bar charts, 1 dimension and 1 measure

Tableau: Workspace Area

Tableau: Connecting to Excel Data

Flowcharting loops, loop counters, kill switches (updated)

Data Retrieval: Scrape data from auto-scrolling websites

Python: Introduction to Google Colab

Python: MLR/OLS assumptions normality multicollinearity VIF

Python: MLR, OLS, standardization, normalization

Python: MLR with categorical values; dummy codes

Python: Intro to MLR / OLS in statmodels.api

New Azure ML Studio: Deploy inference pipeline

New Azure ML Studio: Tune Model Hyperparameters

New Azure ML Studio: Algorithm Selection

New Azure ML Studio: Permutation Feature Importance

New Azure ML: Speed up processing time

New Azure ML Studio: Managing Outliers with Clip Values pill

New Azure ML Studio: Edit meta data, convert ordinal to categorical

New Azure ML Sudio: Math Operation After Modeling

New Azure ML Studio: Regression Model

New Azure ML Studio: Upload and summarize data

New Azure ML Studio: Explore Azure and Create a Machine Learning Workspace

Azure Machine Learning: Sign up for Azure Student Starter Account

Excel: categorical relationships, bar chart, ANOVA, t-test

Excel: numeric to numeric relationships

Excel: multicollinearity; variance inflaction factor (VIF)

Excel: Multiple Linear Regression Example

Excel: prediction calculator from MLR OLS results

Excel: Skew transformed regression MLR OLS

Excel: Including categorical variables in regression

Python: write to sqlite database from pandas dataframe

Python: Converting to and from JSON

Azure ML Studio: Recommender Example: Deployment

Azure ML Studio: Recommender Example: Item Features

Azure ML Studio: Recommender Example: User-Item-Rating Triple

Azure ML Studio: Recommender Example: User Features

Azure ML Studio: Import Data and Summarize Data

Azure ML Studio: Select and Reduce the Dataset

Azure ML Studio: Clean Missing Data pill