PBS -Lucy Worsley’s 12 Days of Tudor Christmas (2019)

PBS -Lucy Worsley’s 12 Days of Tudor Christmas (2019)
English | Size: 1.80 GB
Category: Documentary

Lucy Worsley’s 12 Days of Tudor Christmas
Lucy Worsley recreates how Christmas was celebrated during the age of Henry VIII – eating, drinking, singing, dancing and partying like people did 500 years ago. She is getting into Tudor clothes and inside Tudor minds – discovering the forerunners of some of the Christmas customs we still enjoy today and exploring why other festive traditions fell out of favour.

Udemy – Build Creative Website Using HTML5, CSS3, jQuery & Bootstrap

Udemy – Build Creative Website Using HTML5, CSS3, jQuery & Bootstrap
English | Size: 5.21 GB
Category: Tutorial

*** Over 2500+ Students Are Already Taking This course ***
*** BEST REVIEWED Course on Udemy ***
First thing first, please View Project Demo at link given in lecture# 2 Smiliey
Now, lets discuss what is inside this course. You are here because you are ready to start learning web development skills Or maybe you are already coding and want to take your web development skills to the next level.

Tanner Chidester – Fitness CEO

Tanner Chidester – Fitness CEO
English | Size: 13.78 GB
Category: Tutorial

Discover! How Any Beginner, Amateur And Even Semi Professional Personal Trainer Can Grow Their Fitness Business To 7 Figures In As Little As 12 Months With No Prior Experience

PluralSight – CentOS 7 Courses

PluralSight – CentOS 7 Courses
English | Size: 4.48 GB
Category: Tutorial

CentOS Enterprise Linux 7 Network Management
CentOS Enterprise Linux 7 Operation Essentials
CentOS Enterprise Linux 7 Service Management
CentOS Enterprise Linux 7 Storage Management
CentOS Enterprise Linux 7 User and Group Management
CentOS Enterprise Linux 7 Virtualization Management
Learning the Essentials of CentOS Enterprise Linux 7 Administration

Probabilistic Graphical Model

Probabilistic Graphical Model
English | Size: 2.19 GB
Category: Tutorial

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.