# KDnuggets™ News 16:n26, Jul 20: Bayesian Machine Learning, Explained; Start Learning Deep Learning; Big Data is in Trouble

Bayesian Machine Learning, Explained; How to Start Learning Deep Learning; Why Big Data is in Trouble: They Forgot About Applied Statistics; Data Mining/Data Science "Nobel Prize": 2016 SIGKDD Innovation Award to Philip S. Yu

Features | Software | Tutorials | Opinions | News | Webcasts | Courses | Meetings | Quote

Features

**Bayesian Machine Learning, Explained****How to Start Learning Deep Learning****Why Big Data is in Trouble: They Forgot About Applied Statistics****Data Mining/Data Science "Nobel Prize": 2016 SIGKDD Innovation Award to Philip S. Yu****2016's Best Places for Data Scientist Jobs****KDnuggets Interview: Inderpal Bhandari, IBM Global Chief Data Officer on 4 key ideas of Cognitive Computing**

Software

Tutorials, Overviews, How-Tos

**Predictive Analytics Introductory Key Terms, Explained****In Deep Learning, Architecture Engineering is the New Feature Engineering****Statistical Data Analysis in Python****America's Next Topic Model****MNIST Generative Adversarial Model in Keras**

Opinions

**10 Algorithm Categories for A.I., Big Data, and Data Science****What Data Scientists Can Learn From Qualitative Research****Data Mining Most Vexing Problem Solved, or is this drug REALLY working?****4 Major Trends Disrupting the Data Science Market****What the Next Generation of IoT Sensors Have in Store****What do Postgres, Kafka, and Bitcoin Have in Common?**

News

**Top Stories, July 11-17: Top Machine Learning MOOCs and Online Lectures; Bayesian Machine Learning, Explained****Top KDnuggets tweets, Jul 6 - Jul 12: Statistical Data Analysis #Python #Jupyter Notebooks; Modern Pandas Notebooks****2016 SIGKDD Service Award to Wei Wang**

Webcasts and Webinars

Courses

**Online Master of Science in Predictive Analytics****Online Courses: Big Data Projects and Data Science Pipelines****Metis Data Science Open Houses: San Francisco and New York City**

Meetings

Quote

"In God we trust. All others must bring data." W. Edwards Deming